# TechKis

TechKis is an AI-first software & engineering studio. We build end-to-end platforms and implement AI in your workflows — from LLM agents and RAG assistants to the full-stack web, mobile, desktop and backend services needed to ship them. Actively booking our first 2–3 founding clients.

TechKis is an AI-first software engineering studio. We build end-to-end platforms and implement AI in your workflows — full-stack web apps, mobile apps, desktop apps and backend services, with LLM agents, RAG assistants and workflow automation baked in where they help.

## About TechKis

- **Legal name**: TechKis
- **Type**: Software Engineering Startup
- **Location**: Remote · Global
- **Team**: Small senior team
- **Website**: https://techkis.tech
- **Email**: techkis.tech@gmail.com
- **Status**: actively booking our first 3 founding clients
- **Pricing**: tailored to scope on a 30-minute discovery call — written proposal within 48 hours

## Key numbers

- **AI-first** — Approach
- **Senior** — Team
- **<48h** — Reply time
- **Free** — Strategy call

## Services

### AI Agents & Workflows

_Category: AI & Automation · [Detail page](https://techkis.tech/services/ai-agents-workflows)_

LLM agents that take real action — read your docs, call your APIs, ship work back.

We design and ship LLM agents that do real work — not chatbots that just talk. Built with LangGraph or pure code, evaluated before launch, and observable in production.

**What we deliver:**
- Production-ready agents with tool-use and function calls
- Eval suites covering accuracy, refusal and regression
- Tracing, cost monitoring and structured logs
- Human-in-the-loop gates on anything irreversible
- Safe deployment with rate limits, fallbacks and timeouts

**Tools:** LangGraph · LangChain · OpenAI · Anthropic · Temporal · AWS Bedrock

**Ideal for:**
- Ops teams replacing repetitive manual workflows
- Support orgs automating triage and routing
- Products that need agentic UX baked in

### RAG & Knowledge Assistants

_Category: AI & Automation · [Detail page](https://techkis.tech/services/rag-knowledge-assistants)_

Internal copilots that actually know your company — docs, wiki, Slack, code, with citations.

Retrieval-augmented assistants that answer questions from your real knowledge base. Ingestion pipelines, hybrid semantic + keyword search, access control and source citations on every answer.

**What we deliver:**
- Document ingestion + chunking pipelines
- Hybrid search (vector + BM25) with reranking
- Per-user / per-tenant access control
- Citations and source previews on every answer
- Eval datasets and quality dashboards

**Tools:** pgvector · Pinecone · Qdrant · LangChain · OpenAI Embeddings · Cohere Rerank

**Ideal for:**
- Companies whose docs live across Notion, Slack and GitHub
- Support and success teams answering the same questions
- Sales orgs needing instant access to product knowledge

### Workflow Automation

_Category: AI & Automation · [Detail page](https://techkis.tech/services/workflow-automation)_

Replace manual ops work with AI-augmented pipelines — n8n, Temporal or pure code.

Process automation that combines deterministic logic with LLMs where it actually helps. Built on n8n, Temporal or custom services depending on your stack — with human approval gates baked in.

**What we deliver:**
- End-to-end pipelines from trigger to system of record
- LLM classification, extraction and decision steps
- Human-in-the-loop review queues for sensitive steps
- Retries, idempotency and dead-letter handling
- Audit logs and observability for every run

**Tools:** n8n · Temporal · Make.com · Zapier · Playwright · AWS Lambda

**Ideal for:**
- Ops teams drowning in copy-paste work
- Finance teams processing invoices and receipts
- Marketing teams running repetitive content ops

### AI Strategy & Architecture

_Category: AI & Automation · [Detail page](https://techkis.tech/services/ai-strategy-architecture)_

Find the AI & automation opportunities that actually move your business — then a roadmap to execute.

A short, focused engagement — usually 1–3 weeks — to identify the highest-ROI AI/automation opportunities for your business, score them, and turn the winners into a roadmap your team can actually execute.

**What we deliver:**
- Discovery interviews across teams and workflows
- Opportunity backlog scored on impact vs effort
- Build-vs-buy recommendations per opportunity
- A staged roadmap with concrete first project
- Optional pilot implementation to prove value

**Tools:** Workshops · Process mapping · Opportunity scoring · Build-vs-buy matrices

**Ideal for:**
- Leadership teams overwhelmed by AI hype
- Product teams unsure where AI fits the roadmap
- Ops leaders wanting an honest automation audit

### Full Stack Web Development

_Category: Engineering · [Detail page](https://techkis.tech/services/full-stack-web-development)_

Customer-facing platforms end-to-end — Next.js, React 19 and TypeScript front to back.

Modern web apps built on Next.js App Router with React 19, TypeScript everywhere, and the production polish to actually ship. AI features baked in by default — chat, streaming UIs, structured extraction — where they help.

**What we deliver:**
- Next.js 16 App Router architecture with RSC by default
- Type-safe data layer (Drizzle / Prisma + tRPC or REST)
- Auth, billing, multi-tenant scaffolding
- Streaming UIs and Vercel AI SDK integration
- SEO, OG images, sitemap, JSON-LD and Core Web Vitals tuning

**Tools:** Next.js 16 · React 19 · TypeScript · Tailwind v4 · Drizzle / Prisma · Vercel AI SDK

**Ideal for:**
- Founders shipping a new SaaS product
- Teams rebuilding a legacy web app
- Companies that need design + engineering under one roof

### Mobile App Development

_Category: Engineering · [Detail page](https://techkis.tech/services/mobile-app-development)_

iOS and Android apps — React Native or native — with AI features that actually feel native.

Mobile apps that look native, ship fast and pass App Store / Play Store review on the first try. We default to React Native or Expo for cost-effective cross-platform, native Swift / Kotlin when you need the metal.

**What we deliver:**
- React Native / Expo apps with native modules where needed
- On-device LLM and Whisper integrations
- Offline-first sync, push notifications, deep linking
- App Store and Play Store submission
- OTA updates via EAS or CodePush

**Tools:** React Native · Expo · Swift · Kotlin · Firebase · EAS Build

**Ideal for:**
- Founders shipping their first mobile app
- Teams needing a companion mobile experience
- Products with on-device AI / voice features

### Desktop App Development

_Category: Engineering · [Detail page](https://techkis.tech/services/desktop-application-development)_

Cross-platform desktop apps — Electron or Tauri — with the polish of a native client.

Desktop applications for Windows, macOS and Linux. Electron when you need the rich web stack inside a window, Tauri when you need the smaller binary and tighter OS integration.

**What we deliver:**
- Tauri or Electron app skeleton with auto-update
- Native OS integrations (tray, notifications, shortcuts)
- Code-signing and notarization for macOS / Windows
- Local LLM inference (Ollama / llama.cpp) where it fits
- Telemetry, crash reporting and update channels

**Tools:** Tauri · Electron · Rust · TypeScript · Sqlite · Ollama

**Ideal for:**
- Power-user tools that need to feel native
- Local-first apps with strict data residency
- Products bundling local LLM inference

### API Platforms

_Category: Engineering · [Detail page](https://techkis.tech/services/api-platforms)_

Versioned, documented, well-tested HTTP and event APIs your customers and downstream teams will enjoy.

API-first platforms with proper versioning, generated SDKs, OpenAPI documentation and the operational story (auth, rate limits, idempotency, webhooks) that customers expect.

**What we deliver:**
- REST or GraphQL with auto-generated docs
- OpenAPI spec + typed SDKs (TS / Python / Java)
- Auth (API keys, OAuth2, JWT) and per-tenant rate limits
- Webhook delivery with retries and signing
- Sandbox + production environments

**Tools:** OpenAPI · GraphQL · Spring Boot · Node.js · Kong / AWS API Gateway · Stripe SDK patterns

**Ideal for:**
- Products opening up a platform to third-parties
- Teams formalising internal services into a real API
- Companies that need partner integrations

### Cloud & AWS / DevOps

_Category: Engineering · [Detail page](https://techkis.tech/services/cloud-aws-devops)_

Cloud-native delivery on AWS — IaC, CI/CD, observability and a sensible monthly bill.

Production cloud infrastructure on AWS done right. Terraform for everything, GitHub Actions for CI/CD, OpenTelemetry for observability, and cost guardrails so your AWS bill doesn't surprise you.

**What we deliver:**
- Terraform modules for VPC, ECS/EKS, RDS, S3, CloudFront
- GitHub Actions CI/CD with blue-green or canary deploys
- OpenTelemetry traces, metrics and structured logs
- Cost monitoring with budgets and anomaly alerts
- GPU autoscaling and Bedrock integration for AI workloads

**Tools:** AWS · Terraform · GitHub Actions · ECS / EKS · CloudWatch · OpenTelemetry

**Ideal for:**
- Teams moving off Heroku / Render at scale
- Companies needing SOC 2 / HIPAA-ready infrastructure
- Products with GPU / AI workload requirements

## Use cases we automate

### Customer support

Triage inboxes, draft on-brand replies, route tickets with full context — and escalate only what truly needs a human.

### Internal knowledge

A company-wide copilot that answers from your docs, wiki, Notion and Slack — with citations, access control and audit trails.

### Document & data extraction

Pull structured data from PDFs, contracts, invoices and reports straight into your systems. No more manual entry.

### Sales & outreach

Enrich leads, draft personalised outreach and keep your CRM clean — automatically, with humans approving the sends.

### Content operations

Repurpose long-form into briefs, social posts and newsletters with brand-aware tone, fact checks and a review queue.

### Developer workflows

PR review summaries, ticket triage, changelog generation and intelligent on-call digests — built around your existing tools.

## Industries we serve

### Fintech & Financial Services

Compliance-aware platforms for payments, lending and wealth.

We've worked on payment platforms, lending workflows and risk systems. We default to compliance-aware architecture: audit trails, encryption at rest and in transit, and idempotent money movement.

**We can help with:**
- Payment & ledger services
- AML / KYC document workflows
- Fraud detection with LLMs
- Compliance reporting automation

### SaaS & Developer Tools

Multi-tenant platforms, billing and developer experience.

We build SaaS products end-to-end — multi-tenant data models, Stripe billing, role-based access and the developer-experience polish that lets you charge premium prices.

**We can help with:**
- Multi-tenant data + auth
- Stripe billing & metering
- Public APIs with SDKs
- Dashboards & admin tooling

### Healthcare & MedTech

HIPAA-aware workflows for clinical and patient data.

Patient portals, clinician tooling, document intake and AI assistants that handle PHI responsibly. We design for HIPAA & SOC 2 from day one — not bolted on later.

**We can help with:**
- Patient intake & onboarding
- Clinical document extraction
- AI assistants on PHI
- Audit trails & access control

### Retail & E-commerce

Headless commerce, AI search and personalisation.

Headless commerce builds, AI-powered search and recommendations, and the operational tooling (inventory, returns, support) that real retail businesses need to run.

**We can help with:**
- Headless storefronts (Next.js)
- AI product search & recs
- Inventory & OMS integrations
- Returns + support automation

### EdTech & Learning

AI tutors, content generation and LMS integrations.

Learning platforms with AI-augmented tutoring, content generation pipelines and LMS / LTI / SCORM integrations for institutions.

**We can help with:**
- AI tutoring & feedback loops
- LMS / LTI / SCORM integrations
- Course content generation
- Student knowledge assistants

### Travel & Hospitality

Booking flows, dynamic pricing and AI trip planners.

Booking platforms, dynamic-pricing engines and AI trip-planning assistants — built to plug into the legacy GDS, OTA and PMS systems the industry still runs on.

**We can help with:**
- Booking & checkout flows
- AI trip planners
- Dynamic pricing models
- OTA / GDS / PMS integrations

### Media & Marketing

Content ops, attribution and AI-augmented creative.

Content operations pipelines, marketing-attribution platforms and AI-augmented creative tooling — brand-aware, with humans approving the sends.

**We can help with:**
- AI content pipelines
- Brand-aware copy generation
- Attribution & analytics
- CMS & MarTech integrations

### Logistics & Operations

Document processing, dispatch and workflow automation.

Document-heavy operations: invoices, bills of lading, customs forms. We replace manual entry with AI extraction and human approval — fewer errors, faster cycle times.

**We can help with:**
- Document data extraction
- Dispatch & routing tools
- OCR + LLM verification
- Operational dashboards

## Capabilities

### AI & ML Engineering

Senior LLM engineering — from agent design to production observability. We pick the right model and tools for your problem, not a fixed vendor stack.

- **LLM agents & tool-use** — Orchestration with any modern agent framework
- **RAG pipelines** — Hybrid search, reranking, citations
- **Vector search** — Any vector DB — pgvector, Pinecone, Qdrant and others
- **Evals & benchmarks** — Regression suites, drift alerts, golden sets
- **Fine-tuning & adapters** — LoRA, SFT, RLHF where it genuinely helps
- **Multimodal** — Vision, voice, audio across leading providers
- **Prompt engineering** — Templates, guardrails, structured output
- **Cost & latency tuning** — Model routing, caching, batching

### Backend Engineering

Production backends with the observability and resilience real systems need. JVM, Node or Python — we work in whatever fits the problem.

- **JVM services** — Spring Boot, Java, Kotlin — modern JVM
- **Node & TypeScript APIs** — Fastify, NestJS, Express
- **Python services** — FastAPI, Django, async-first
- **Microservices & DDD** — Clean domain boundaries
- **Event-driven systems** — Kafka, RabbitMQ, SQS and others
- **REST & GraphQL APIs** — OpenAPI, typed SDKs
- **Relational databases** — PostgreSQL, MySQL, schema design
- **Caching & queues** — Redis, Memcached, background workers
- **Observability** — OpenTelemetry, Prometheus, Grafana

### Frontend, Mobile & Desktop

Modern clients — accessible, fast, AI-ready. We work in the framework and platform that fits your team and product, not a single fixed stack.

- **Modern web frameworks** — Next.js, Remix, Astro and similar
- **TypeScript front-to-back** — React, Vue, Svelte — type-safe
- **Design systems & theming** — Component libraries, tokens, dark mode
- **Streaming AI UIs** — Server-driven streaming, leading AI SDKs
- **Cross-platform mobile** — React Native, Expo, Flutter
- **Native iOS & Android** — Swift, Kotlin where they earn their keep
- **Cross-platform desktop** — Tauri, Electron, auto-update channels
- **Accessibility** — WCAG 2.2 AA, keyboard-first, screen-reader tested

### Cloud & DevOps

Cloud-agnostic infrastructure, IaC and CI/CD — with cost guardrails baked in. We meet your cloud where it is.

- **Cloud platforms** — AWS, Azure, GCP — managed where it helps
- **Infrastructure as code** — Terraform, Pulumi, CloudFormation
- **CI/CD pipelines** — GitHub Actions, GitLab, blue-green, canary
- **Containers & orchestration** — Docker, Kubernetes, ECS, serverless
- **Compliance readiness** — SOC 2, HIPAA, GDPR audit trails
- **Cost optimization** — Budgets, anomaly alerts, rightsizing
- **Secrets & identity** — IAM, KMS, Vault, OIDC, SSO
- **GPU autoscaling** — For inference and training workloads

### Product & Architecture

The cross-cutting work that decides whether a project succeeds long after delivery.

- **System design reviews** — Independent audits
- **Migration & modernization** — Off legacy, onto cloud
- **Performance engineering** — p95 latency, query tuning
- **Security audits** — Threat modelling, secrets hygiene
- **Technical due diligence** — For acquirers and investors
- **ADRs** — Decision logs your future team will thank you for
- **Design systems** — Component libraries, tokens
- **Documentation** — Runbooks, API docs, onboarding

## Custom Software Development deep dive (https://techkis.tech/capabilities/custom-software-development)

We design and build custom software end-to-end — web, mobile, desktop and the APIs behind them. AI features baked in where they help. Senior engineers, written architecture, weekly demos and production-grade rigour from day one.

### What you gain

- **Tailored to your problem** — No template SaaS, no offshore handoff. We design for the specific workflow, integration and user you're shipping to — not the generic case.
- **Cloud-native by default** — AWS, multi-AZ, infrastructure-as-code. Built to scale horizontally and be redeployed in minutes — not pinned to a single box.
- **AI where it actually helps** — Smart extraction, assistive UX, summarization, structured outputs — wired in deliberately, with evals, not sprinkled in for the demo.
- **Built for the long run** — Type-safe code, CI/CD, observability and tests. The codebase a competent team can keep building on for years — not a dead-end you'll rewrite.
- **Architecture-first** — We write the architecture document before the first line of feature code. You'll know exactly what's being built, why and what trades it makes.

### What we build

#### Web development

Customer-facing platforms, internal tools, SaaS products and dashboards built on the modern web framework that fits your team — React, Vue or Svelte, with TypeScript end-to-end. Streaming UIs, type-safe data layers, auth, billing and multi-tenant scaffolding — production-grade from day one.

- Modern web frameworks — pick what fits your team
- Type-safe data layer end-to-end
- Auth, billing and multi-tenant scaffolding
- SEO, accessibility and Core Web Vitals tuning

Linked service: https://techkis.tech/services/full-stack-web-development

#### Mobile application development

Native-feeling iOS + Android apps built cross-platform where it makes sense, and native Swift / Kotlin where it earns its keep. AI-driven personalization, offline-first, deep linking and push notifications baked in.

- Cross-platform (React Native, Expo, Flutter) or native
- Offline-first sync with conflict resolution
- Push notifications and deep linking
- App Store and Play Store submission and review

Linked service: https://techkis.tech/services/mobile-app-development

#### Desktop applications

Cross-platform desktop apps — small footprint, OS-level integrations, auto-update channels and code-signed installers for Mac, Windows and Linux. Ideal for power-user tools and AI assistants that need local context.

- Cross-platform (Tauri, Electron) or native
- Auto-update channels and code-signed installers
- OS-level menus, tray icons and shortcuts
- Local AI inference where privacy matters

Linked service: https://techkis.tech/services/desktop-app-development

#### Backend & microservices

JVM, Node or Python microservices designed for scale from day one — we work in whatever fits your team and existing platform. Event-driven where it helps, observable everywhere, with clean domain boundaries and idempotent data flows.

- JVM, Node or Python — whichever fits your stack
- Domain-driven service decomposition
- OpenTelemetry traces, metrics and structured logs
- CI/CD with blue-green or canary deploys

Linked service: https://techkis.tech/services/undefined

### What you can achieve

- **01 Validate your vision** — We can start with a 2–4 week proof-of-concept — clickable prototype, AI feasibility test or thin-slice MVP — before committing to a full build.
- **02 Ship fast, ship well** — Weekly sprints behind feature flags. Working software in front of real users within weeks, not quarters.
- **03 Future-proof your stack** — Modern foundations (Next.js, React 19, Java 21, AWS) and CI/CD pipelines that make the next year of changes feel boring — not terrifying.
- **04 Maximize operational efficiency** — Process automation, smart admin tooling and AI-augmented workflows wired into the product — so your team scales without scaling the headcount.
- **05 Build on solid architecture** — Written architecture docs, clear domain boundaries and documented trade-offs. The codebase a competent team can keep building on for years.
- **06 Stay resilient** — Observability, health checks, rollback paths and on-call runbooks from day one — so production stays boring even when traffic isn't.

### Six steps, from kickoff to production.

Every custom software engagement follows the same outline — adapted to your timeline, stack and risk tolerance. No black boxes.

#### 01 Discovery & planning

Deep dive into business goals, users, constraints and integrations. Output: written scope, feasibility notes, a roadmap and the architecture document for what we'll actually build.

#### 02 Design & prototyping

Interactive wireframes and a clickable prototype reviewed with you. We validate usability, edge cases and AI/data assumptions before writing feature code.

#### 03 Build

Agile sprints behind feature flags. Type-safe code, automated tests, peer review on every PR, and a public changelog you can read at any time.

#### 04 Testing & QA

Functional, performance, security and user-acceptance testing. We hunt vulnerabilities before launch — not after a postmortem.

#### 05 Deployment

Zero-downtime releases with CI/CD, infrastructure-as-code and blue-green or canary deploys. Production gets boring, the way it should.

#### 06 Support & maintenance

Monitoring, dependency upkeep, security patches and a 30-day support window — or an ongoing retainer for new features and tuning.

## Experience Transformation deep dive (https://techkis.tech/capabilities/experience-transformation)

We help teams move beyond clunky legacy software — without rewriting everything from scratch. Cloud migration, UI/UX redesign, intelligent automation and clean data pipelines, delivered as one coordinated programme rather than four disconnected projects.

### What you get

- **Custom-fit to your business** — We modernize the bits that hurt and leave alone the bits that don't. No template rewrite, no rip-and-replace just because a vendor said so.
- **Scale without overhauls** — Cloud-native infrastructure and horizontal-scale architecture so the next round of growth doesn't trigger another expensive rebuild.
- **Exceptional user experience** — Modern, accessible, fast interfaces that your team and customers actually want to use — designed against real user research, not gut feeling.
- **Seamless integration** — We meet your existing stack where it is — ERPs, CRMs, legacy databases, third-party APIs — and connect the dots without making everyone rewrite their tools.
- **Data-driven ROI** — We measure performance gains and operational cost savings — and we instrument the new system so you can keep measuring after we leave.

### What we do

#### Revitalize legacy systems

Outdated systems slow your business and limit growth. We move them to cloud-native architecture, strangle them with a modern facade, or rewrite the parts that are holding you back — without a year-long freeze on shipping new features.

- Cloud migration to AWS / Azure / GCP
- Strangler-fig refactoring instead of big-bang rewrites
- Database modernization (Oracle/MSSQL → PostgreSQL)
- Containerization and orchestration on Kubernetes/ECS

#### Enhance user experience

A seamless digital experience is the difference between users tolerating your product and recommending it. We research, prototype and ship interface redesigns optimized for accessibility, performance and conversion.

- User research, journey mapping and information architecture
- Component-library design system (Figma → code)
- WCAG AA accessibility from the ground up
- Core Web Vitals and performance budgeting

#### Process automation

Manual processes slow productivity and multiply errors. We automate the workflows that actually hurt — using deterministic logic where it suffices and LLMs where they genuinely help — with human approval gates on anything sensitive.

- End-to-end workflow pipelines on n8n / Temporal / pure code
- LLM classification, extraction and decision steps
- Human-in-the-loop review queues for sensitive steps
- Audit logs, retries and idempotency built in

#### Data integration

Siloed data limits insights and decision-making. We connect the systems, unify the schemas and build pipelines you can trust — feeding analytics, AI features and operational tools from one clean source of truth.

- ETL / ELT pipelines on Airflow / dbt / Dagster
- CDC streams to data warehouse or lake
- Schema modeling and data quality monitoring
- Single-source-of-truth feeds for BI and AI features

### What you can achieve

- **01 Revitalize legacy systems** — Get off unsupported platforms, retire technical debt and free the team from the constant maintenance tax.
- **02 Boost efficiency** — Automate the busywork so your people can spend time on the work that actually moves metrics.
- **03 Enhance user experience** — Modern interfaces that customers and staff want to use — measured against real research, not opinions.
- **04 Enable future-readiness** — Cloud-native foundations that the next AI feature, the next acquisition, the next pivot can build on cleanly.
- **05 Drive competitive advantage** — Faster iteration, lower marginal cost per transaction and product capabilities your incumbent competitors can't match.
- **06 Ensure seamless transition** — Strangler-fig migration paths, blue-green deploys, dual-write windows and rollback plans — so the lights stay on while we modernize underneath.

### Seven steps, from audit to live.

Modernization that doesn't put your operation at risk. Every step has a written gate — nothing moves forward until both teams agree it should.

#### 01 Discovery & assessment

We audit the existing system end-to-end — code, data, users, integrations and pain points. Output: a written assessment with prioritized risks and a 'don't break this' list.

#### 02 Strategy & roadmap

We design the modernization strategy aligned to your business priorities — milestones, cutover plan, rollback paths and the resource shape needed to get there.

#### 03 UI/UX design & prototyping

We redesign the surfaces that matter, validate with real users, and ship the design system that the new product hangs off.

#### 04 Technology modernization

Cloud migration, framework upgrades, database modernization and AI integration — done incrementally with feature flags, not as a single big-bang cutover.

#### 05 Testing & optimization

Functional, performance and security testing on every release. Performance budgets and SLOs defined and monitored, not assumed.

#### 06 Deployment & integration

Zero-downtime cutover with blue-green or canary deploys. Integration smoke tests run on every release — not just at the end.

#### 07 Ongoing support & monitoring

Continuous monitoring, security patching and a proactive optimization cadence. We can stay on retainer or hand over to your team — your call.

## Founding Partner Program (https://techkis.tech/capabilities/founding-partner-program)

TechKis is a brand-new AI-first software studio actively booking our first 2–3 founding clients. In exchange for being a flagship reference, you get founder-friendly terms, a senior team's full attention and direct access to the people writing the code — not a sales layer.

### What you get

- **Co-create your product** — We refine your idea, sharpen the wedge and design the MVP with you — combining product workshops, technical feasibility and AI opportunity mapping. The output is a written scope and roadmap you can hold us to.
- **Sprint to a working MVP** — A focused 4–8 week sprint to ship a working MVP — agile delivery, weekly demos behind flags and AI features baked in where they actually help. Built on Next.js, React 19, Spring Boot or whatever your roadmap demands.
- **Founder-friendly terms** — Discount, milestone-based billing or a hybrid arrangement on our first 2–3 engagements while we build our portfolio. Concrete numbers stay offline — but the trade is simple: lower cost in exchange for being our flagship case study.
- **Scale & support beyond launch** — Post-MVP support, hardening and growth work on a retainer if it's a fit. We don't disappear after launch — and we don't get in the way of you scaling the team in-house when the time comes.

### Three steps, from idea to launched MVP.

We keep the operating model simple — three phases, weekly cadence, written outputs at every gate.

#### 01 Co-discover

Intensive workshops to refine the vision, map the user, score AI opportunities and write the architecture. Output: an MVP scope you actually want to build, with edge cases and trade-offs on paper.

#### 02 Co-build

An agile sprint with weekly demos behind feature flags. We ship to real users early, gather feedback, and bake in AI, evals and observability from day one — not as an afterthought.

#### 03 Co-operate

Launch, monitor, learn. Post-MVP we move into a smaller retainer for tuning, new features and supporting the team you'll eventually hire to take it over.

### What it feels like, phase by phase.

A founding engagement isn't a transaction — it's a working relationship. Here's how each phase actually plays out for you.

#### 01 Spot the opportunity

We meet, listen, ask the awkward questions and write back our honest read of the opportunity within a week. If we don't think we're the right partner, we'll tell you.

#### 02 Build fast, pivot smarter

Working software in front of real users within weeks. Weekly demos, written changelogs and decision logs. Every assumption gets tested against real usage, not slide decks.

#### 03 Break technical barriers

We handle the scaling questions, the AI evals, the security review and the architecture upgrades — so your team can stay focused on customers and product.

#### 04 Win or learn — together

Some bets land, some don't. Either way you walk away with shipped software, real user feedback and a senior team that helped you make the call — not a vendor who disappeared at the contract end.

## AI Services deep dive (https://techkis.tech/capabilities/ai-services)

We help teams move from AI experiments to production. From LLM agents and RAG copilots to automated workflows and decision systems — built with evals, observability and senior craft so it actually holds up in production.

### What you get

- **Automate repetitive work** — Eliminate manual copy-paste across tools — ticket triage, document extraction, lead enrichment, content ops — with pipelines that combine deterministic logic and LLMs where each helps most.
- **Accelerate decisions with data** — Turn fragmented signals into clear recommendations. Forecasting, anomaly detection, ranking and prioritization — surfaced where your team already works.
- **Personalize at scale** — Tailor experiences for each customer without hiring an army. Recommendations, dynamic copy, smart onboarding and assistive UX that adapts to context.
- **Unify fragmented knowledge** — Connect Notion, Slack, Drive, GitHub, Zendesk and your data warehouse into one searchable assistant — with access control and source citations on every answer.
- **Stay competitive with AI** — Avoid AI theatre. Get a focused roadmap of the AI opportunities that move metrics, scored on impact vs effort — with the team to execute the winners.

### What we do

#### AI-driven process automation

Agentic workflows that do real work — read your docs, call your APIs, write back to systems of record. LangGraph or pure-code orchestration, tool-use everywhere, human-in-the-loop gates on anything irreversible. Built with evals before launch and tracing once it's live.

- Agent orchestration with LangGraph or Temporal
- Tool-use and function calls across your stack
- Human-in-the-loop approval queues
- Eval suites covering accuracy, refusal and regression

Linked service: https://techkis.tech/services/ai-agents-workflows

#### AI-powered virtual assistants

Internal and customer-facing assistants that actually know your company. Retrieval-augmented generation on your real knowledge base, hybrid semantic + keyword search, per-tenant access control and source citations on every answer — not vibes.

- Hybrid search (vector + BM25) with reranking
- Document ingestion + chunking pipelines
- Per-user / per-tenant access control
- Citations and source previews on every answer

Linked service: https://techkis.tech/services/rag-knowledge-assistants

#### Predictive AI for smarter decisions

Where models genuinely beat heuristics, we build them. Forecasting, classification, anomaly detection and ranking — wrapped in pipelines you can retrain, monitored for drift, and integrated into the surface where the decision actually happens.

- Build-vs-buy analysis for every model choice
- Retraining pipelines with feature stores
- Drift monitoring and quality dashboards
- Decisions wired into the product, not a notebook

Linked service: https://techkis.tech/services/ai-strategy-architecture

#### AI-driven data integration & insights

Stitch fragmented data sources into a single trustworthy view, then layer AI on top to extract, classify and route automatically. Built on n8n, Temporal or pure code depending on your stack — with retries, idempotency and audit logs baked in.

- End-to-end pipelines from trigger to system of record
- LLM classification, extraction and decision steps
- Retries, idempotency and dead-letter handling
- Audit logs and observability for every run

Linked service: https://techkis.tech/services/workflow-automation

### Why TechKis for AI

- **01 Faster time-to-value** — We ship behind feature flags every week — so AI features reach real users sooner, not after a six-month research project.
- **02 Measurable AI outcomes** — Every AI feature ships with evals and a regression suite. You'll know when the model drifts — before customers do.
- **03 Stronger customer experiences** — From assisted support to personalized onboarding — AI surfaces that feel like a teammate, not a chatbot.
- **04 Operational resilience** — Idempotent pipelines, retries, dead-letter queues and tracing. AI workflows that survive flaky APIs and noisy inputs.
- **05 Lower marginal cost per task** — We pick the right model for the job — small + distilled where it works, frontier where it has to. With cost monitoring and budgets per workflow.
- **06 Architecture that scales** — We design the platform once, well — model providers, eval harness, observability and access control — so adding the next AI feature is a week, not a quarter.

### A six-step process, from idea to production.

Every AI engagement follows the same outline — adapted to your stack and risk tolerance. No black boxes, no surprise pivots.

#### 01 Exploration & discovery

We map the workflows, data, constraints and stakeholders. Output: an opportunity backlog scored on impact vs effort, and a clear 'don't do this yet' list.

#### 02 Strategy & roadmap

We pick the first 2–3 projects, decide build-vs-buy per opportunity, and write the AI architecture that the rest of the work hangs off — model providers, evals, observability, access control.

#### 03 Model & system design

We design the prompts, retrieval, tools, schemas and guardrails — and the eval dataset that defines 'good enough to ship'. Reviewed with you before a line of feature code is written.

#### 04 Build & integrate

Weekly sprints behind feature flags. We integrate into your real systems — auth, data, APIs — not a sandbox demo. Every step shipped with tests and observability from day one.

#### 05 Eval & optimize

We run the eval suite on every change, tune cost vs quality vs latency, and pilot with a small user cohort. Nothing scales to all users until evals and pilot metrics agree.

#### 06 Operate & evolve

Production launch with monitoring, drift detection, fallbacks and a clear on-call runbook. Optional retainer for tuning, new features and adapting to new model releases.

## About TechKis

TechKis is a brand-new AI-first software & engineering studio. We started TechKis because most agencies bolt AI on as an afterthought, and most AI consultants don't ship code. We do both — production-ready software with AI built in from the start.

### Mission

Software is changing faster than most teams can keep up. AI now reshapes how products are built, supported and operated — but the gap between a working demo and a reliable, production-grade AI feature is bigger than ever. TechKis helps ambitious founders and product teams cross that gap with senior craft, real engineering rigour and zero hype.

### What we believe

- **AI-first by default** — We start every engagement asking 'where does AI or automation actually help here?'. If the answer is 'it doesn't', we say so.
- **Senior engineers only** — No juniors, no offshore handoff. The engineers who scope your project are the same people writing prompts and code.
- **Evals over vibes** — Every AI feature ships with measurable evals and a regression suite. You'll know when the model drifts — before customers do.
- **Radical transparency** — Weekly demos, written changelogs, decision logs. Nothing happens behind the curtain.
- **One project at a time** — We deliberately take on a small number of engagements so each gets full attention from a senior team.

### The team

We're a small, senior team. The founders have been building production software for years, and shipping with LLMs since GPT-3. We work fully remote and overlap with US, EU and APAC working hours.

### Founding-client invitation

We're actively booking our first 2–3 founding clients. To make it worth working with a brand-new studio, we're offering founder-friendly terms on our first engagements while we build our portfolio — details we'll share on a scoping call. If you're a founder or product leader who wants senior craft at startup velocity, we'd love to talk.

## Technology stack

### AI & LLM

- OpenAI
- Anthropic
- LangChain
- LangGraph
- pgvector

### Automation

- n8n
- Temporal
- Playwright
- Make.com
- Lambdas / Cron

### Backend & Data

- Java
- Spring Boot
- Node.js
- PostgreSQL
- Redis

### Frontend & Cloud

- Next.js
- React
- TypeScript
- AWS
- Docker

## How we work

### 01. Discovery & AI fit

A focused 30-minute call to map the AI / automation opportunities that actually move your business — and the ones that don't.

### 02. Proposal & eval plan

Within 48 hours: written scope, milestones, deliverables, a fixed-or-time-boxed estimate and the evaluation criteria for every AI feature.

### 03. Weekly AI sprints

Ship AI features behind flags every week — evaluated before they touch production users, with public changelog and decision logs.

### 04. Launch & guardrails

Production launch with monitoring, evals, fallbacks and a 30-day support window — or an ongoing retainer for tuning and new features.

## Our founding-client promise

### AI-first by default

Every engagement starts with 'where does AI or automation actually help?'. If the answer is 'it doesn't here', we say so. No AI-for-show.

### Senior, AI-fluent engineers

We've been building with LLMs since GPT-3. No juniors, no offshore handoff. The engineers who scope your workflow write the prompts and the code.

### Evals over vibes

Every AI feature ships with measurable evals and a regression suite. You'll see when the model drifts — not weeks after a customer complains.

### Founding-client offer

Our first 2–3 engagements get founder-friendly terms — meaningful incentives we discuss directly on a scoping call. Senior craft at startup-friendly conditions.

## Why work with us

- Senior engineers building with LLMs since GPT-3
- AI-first: agents, RAG and automation as default tools
- Evals over vibes — every AI workflow measured
- Full stack: Java Spring Boot · Next.js · AWS · LangGraph
- Architecture-first — we design before we ship
- Founder-friendly terms on our first 2–3 engagements

## Frequently asked questions

### Will AI workflows actually work reliably in production?

Yes, with the right approach: tight scope, evals before launch, human-in-the-loop on anything irreversible, fallbacks for model failures, and observability so you see drift before customers do. That's the bar we hold ourselves to.

### What does TechKis do?

We build end-to-end platforms and implement AI in your workflows.

### How do you price projects?

We tailor pricing to scope on a 30-minute discovery call rather than publishing rate cards online. Send us the brief and we'll come back with a written, fixed-or-time-boxed proposal within 48 hours — including a founder-friendly offer for our first 2–3 founding clients.

### Is TechKis a new company?

Yes — we're a brand-new studio actively looking for our first founding clients. Our founders are senior engineers who've been building with LLMs since GPT-3, with prior experience at product startups. We're offering founder-friendly terms on our first 2–3 engagements while we build our portfolio — happy to discuss details on a scoping call.

### Do you have client case studies yet?

Not under the TechKis name yet — we're a new studio looking for the founding clients we'll write our first case studies with. Our founders bring senior engineering experience from prior roles at product startups, which is the credibility we lead with today.

### How does an engagement start?

We hop on a 30-minute scoping call, then send a written proposal with scope, milestones, deliverables, evaluation plan and a fixed or time-boxed estimate within 48 hours.

### Do you work with existing in-house teams?

Absolutely. We plug into your Git, Slack, Linear/Jira and CI workflows, pair with your engineers, and try to leave them more capable than we found them — especially on AI tooling and evals.

### What is the typical project timeline?

Most engagements run 4–12 weeks. We work in weekly sprints with a public changelog so you always know where things stand.

### Do you offer ongoing support after launch?

Yes — flat-rate monthly retainers for maintenance, eval monitoring, model upgrades and incremental feature work once the initial delivery is live.

## Insights (https://techkis.tech/insights)

Engineering notes and field reports from the TechKis team. Each post lives at `https://techkis.tech/insights/<slug>`.

### Google I/O 2026 — what stood out to our team

- **URL**: https://techkis.tech/insights/google-io-2026-highlights
- **Published**: 2026-05-22
- **Reading time**: 8 min read
- **Author**: The TechKis team
- **Tags**: Google I/O, Gemini, AI Engineering, Android, Web Platform

Our take on the Google I/O 2026 announcements that actually matter for shipping AI-first software in production — Gemini, Android, web platform and developer tooling.


Google I/O is the year's clearest signal of where the platform is heading. We watched the keynotes, dug into the developer sessions and pulled out the four threads we think actually change how we build for clients in the next 12 months.

This isn't a transcript — Google's announcements page covers that. It's our **so-what** filter: what's going to land in real production code, what's a year out, and what's noise.

## 1. Gemini keeps getting more capable, and cheaper

The headline every I/O for the last three years has been the next Gemini family. This year was no different, with another step-change in reasoning, longer context and stronger tool use. The pattern that matters to us is the **cost curve**: features that were premium two model generations ago now sit in the mid-tier — which is the tier most production AI features should actually run on.

![Gemini model generations migrate outward over time: each new release pushes the prior tier's capabilities into a cheaper, more accessible default.](figure:gemini)

What that means for us:

- We're more aggressive about defaulting to the mid-tier for everything except the genuinely hard reasoning steps.
- Long-context use cases that were uneconomic in 2024 (think: feed-the-whole-repo-and-ask-it-questions) are increasingly viable. We're now writing them into RAG-replacement evaluations rather than RAG-mandatory ones.
- Tool calling reliability keeps climbing — the gap between "demo works" and "shipped agent works on 95% of inputs" is finally narrowing without bespoke retries and re-prompts.

The honest catch: cheaper doesn't mean free, and the new models aren't universally better at everything. We still run our own eval suite on every model swap. The press release isn't the eval.

## 2. On-device AI gets serious on Android

Android's bet on running models on the device — not the cloud — is finally hitting a useful tier. The combination of stronger NPU hardware and smaller, more capable models means the latency and privacy story for on-device features has improved meaningfully.

![Running inference on-device removes the server hop — privacy, latency and unit economics all move in the same direction.](figure:on-device)

For us this matters in three concrete ways:

- **Privacy-sensitive workflows** (legal, medical, financial assistive features) become viable to ship without a server hop.
- **Latency-critical UX** (live transcription, suggestion-as-you-type, camera-frame analysis) feels native rather than tethered.
- **Cost** — for high-volume, low-margin features, on-device inference flips the unit economics.

The constraint hasn't changed: you have to think about model size, memory pressure and battery from day one. But the envelope of "what can ship on a mid-range Android phone in 2026" is a lot bigger than it was in 2024.

## 3. The web platform is quietly catching up

The web platform announcements at I/O rarely make headlines, but they cumulatively matter more than any single Gemini delta. This year we paid attention to:

![Modern web platforms now stream AI responses while staying inside tight Interaction-to-Next-Paint budgets.](figure:web-platform)

- **Continued Core Web Vitals tightening** — the INP (Interaction to Next Paint) metric is now firmly the bar to clear, and the budgets are tighter. Our build defaults already pass it; teams running on older stacks should plan a migration.
- **Better native streaming UI primitives** — closer alignment with what we already do with React Server Components, Vercel AI SDK and friends.
- **WebGPU is finally something to plan around** — not yet a default, but for the right workload (in-browser inference, complex visualisations) it's no longer a science project.

The pattern: the web is becoming a more capable surface for the kind of AI-augmented products we build, while staying the most accessible distribution channel on the internet. We're not abandoning native — but the "ship a web app first, native if you must" calculus keeps getting stronger.

## 4. Developer tooling: AI in the inner loop

The most under-appreciated thread at I/O this year was developer tooling. The IDE story, the test-generation story, the codebase-aware assistants — all of it took a step forward. We're already deep users of AI-augmented dev workflows, and the new generation closes some of the rough edges:

![AI in the inner loop: refactors, tests and docs generated alongside the code, not after it.](figure:dev-tooling)

- **Refactors that span multiple files** that actually understand the architecture, not just the syntax.
- **Tests that interrogate intent**, not just lines of code.
- **Documentation that stays in sync** with the codebase, generated on commit.

For us, this changes the math on what we can deliver in a 4-week sprint. A senior engineer with the right AI dev loop now does what a 2-person team did 18 months ago — without losing the architectural rigour that the second person was supposed to bring.

## What we're not doing yet

A few things we saw and are not (yet) putting on client roadmaps:

![Where we ship now vs. where we are deliberately waiting until the platform settles.](figure:stack-bets)

- **Anything that requires very-bleeding-edge model features** in production paths. We give them 3–6 months to stabilise before relying on them.
- **Heavy bets on early-stage Android features** that don't yet ship on a majority of devices our clients' users own.
- **Replacing well-tuned retrieval with massive context windows** by default — long-context is a tool, not a strategy. We still pick per-problem.

## TL;DR

![Where the platform is heading: senior craft + AI-augmented engineering + the web as a default distribution surface compounding over the next few years.](figure:roadmap)

The platform keeps moving in the direction we bet on when we started TechKis: AI-augmented engineering becomes the default, the web stays the most cost-effective distribution surface, and senior craft compounds with every model generation. Google I/O 2026 didn't shift our roadmap — it confirmed it.

If you're a founder or product team thinking about where to spend AI engineering budget in the next 12 months, [we'd love to talk](/#contact).


## Contact

- **Email**: techkis.tech@gmail.com
- **Website contact form**: https://techkis.tech/#contact
- **LinkedIn**: https://www.linkedin.com/company/tech-kis/