Every layer of an AI product. One accountable team.
Seven capabilities that cover strategy, models, agents, data, cloud and the applications your users touch, so nothing falls between vendors.
Choose the model that fits your vision
Fixed scope when the outcome is clear, a dedicated team when the roadmap is alive, or senior engineers inside your own squad.
Fixed-scope pilot
A defined outcome, timeline and price after the deep-dive sprint. Best for a first system.
- Scoped from the audit and architecture doc
- Weekly demos and releases
- Fixed price with change control
Dedicated AI team
A cross-functional squad embedded with your product team for a quarter or longer.
- AI, data, product and design in one team
- Monthly retainer, flexible roadmap
- Knowledge transfer built in
Staff augmentation
Senior AI or data engineers who join your team and your rituals from week one.
- Time-zone aligned
- Start within two weeks
- Scale up or down monthly
AI doesn't fail at ideas. It fails at execution.
Every engagement follows a path from concept to scale with success defined up front, weekly releases and no surprises.
Discover
A 60-minute call and a deep-dive sprint that end in a scored opportunity map and a baseline.
Design
Architecture and stack chosen with a decision matrix and a model bake-off on your data.
Build
Weekly releases into your environment with evals, guardrails and traces from sprint one.
Scale
Hardening, staged rollout, cost controls and handover so your team runs it.
Building on proven, scalable foundations
The strength of any AI system lies in the technology behind it. We choose per workload, benchmark on your data, and build so you can switch.
- Python
- TypeScript
- Node.js
- Go
- Rust
- SQL
- Bun
- Swift
- Kotlin
- Solidity
- OpenAI GPTGPT-4o family
- Anthropic Claude
- Google Gemini
- Meta Llama
- Mistral
- DeepSeek
- Hugging Face
- Ollama
- Groq
- NVIDIA
- LangGraphMulti-agent workflows
- LangChain
- LlamaIndex
- FastAPI
- Next.js
- React
- PyTorch
- TensorFlow
- scikit-learn
- MCPModel Context Protocol
- RAGHybrid retrieval + RRF
- Structured outputsSchema-first AI
- PostgreSQL+ pgvector
- Pinecone
- Weaviate
- Qdrant
- Elasticsearch
- Redis
- MongoDB
- Snowflake
- Databricks
- Apache Spark
- Apache Airflow
- Apache Kafka
- dbt
- AWS
- Google Cloud
- Microsoft Azure
- Docker
- Kubernetes
- Terraform
- Vercel
- Cloudflare
- GitHub Actions
- Grafana
- Prometheus
- Sentry
- Langfuse
- LangSmith
- Promptfoo
- MLflow
- Weights & Biases
- Cursor
- Claude Code
- GitHub Copilot
- Playwright
- Figma
- Shopify
- Razorpay
- Stripe
- HubSpot
- Zoho
- Salesforce
- Zapier
- n8n
- Make
- Slack
- Notion
- Ethereum
- Solana
- Polygon
- Hyperledger
- Solidity
- OpenZeppelin
- Chainlink
- IPFS
- Alchemy
- Hardhat
Get the clarity you deserve
Straight answers to the questions we hear most. Ask us anything else on a call.
Nothing breaks. The stack is standard and agreed up front, everything is deployed into your own cloud accounts as we go, and you receive a handover pack: architecture decision records, end-to-end documentation with timings, runbooks, evaluation reports, traces and cost dashboards, infrastructure as code and recorded walkthroughs. Your team, or the next vendor, inherits a documented system.
Nothing breaks. The stack is standard and agreed up front, everything is deployed into your own cloud accounts as we go, and you receive a handover pack: architecture decision records, end-to-end documentation with timings, runbooks, evaluation reports, traces and cost dashboards, infrastructure as code and recorded walkthroughs. Your team, or the next vendor, inherits a documented system.
Let's build intelligent systems that drive growth
Tachyon is the engineering partner for teams that need AI in production, not in a deck. Start with a free 60-minute discovery call.