How we work
From first call to working system.
Every project follows the same path: understand the problem, prove the approach on your own data, then build it properly. You can stop after any stage, and every stage gives you something you can evaluate.
Ways to work with us
Start small, scale on evidence.
Discovery call
Tell us the problem. We give you an honest view of whether AI, automation or plain software is the right fix, and what it would take.
Proof of concept
A short build tested on your real cases, measured against a target agreed up front. It ends in a clear go or no-go.
Production build
The proven approach built properly: tests, monitoring, guardrails and the integrations that make it part of your systems.
Support or handover
A supervised rollout, then a clean handover to your team or ongoing support from us.
Already have an engineering team? We also run architecture reviews and build-versus-buy assessments.
Our process
From discovery to production.
You are never more than one stage away from stopping, and every stage produces something you can evaluate.
Discover
We map the workflow, the data and the limits. Then we agree what a good result looks like, as a number rather than a feeling.
Prove
A short build against your real cases, measured on that number. It ends in a clear go or no-go, with the evidence attached.
Build
The proven approach built properly: tests, observability, guardrails and the integration work that makes it part of your stack.
Run
A supervised rollout, with monitoring and human escalation in place. Then a clean handover to your team, or ongoing support from us.
What you need to start
- The problem you want solved, and what a good result looks like.
- A handful of real example cases or sample data to test against.
- One person on your side who knows the process and can answer questions.
No technical specification needed. We help define it.
How we measure success
- We agree how success will be measured before we build.
- We test on your real cases, not on a demo.
- We report the result against that measure, including when it falls short.
- If we cannot back a claim with evidence, we leave it out.
Confidentiality
We sign NDAs before reviewing sensitive information. Client work is shared only with the client’s permission, and access to your data is limited to the people who need it.
Technology we use
The stack we build on.
We choose the simplest technology that delivers the result. These are the tools we reach for most, along with the retrieval (RAG) and agent patterns we build on them.
AI models, agents & automation
Claude
GPT
Gemini
Vertex AI
LangChain
LangGraph
LlamaIndex
CrewAI
n8n
LiteLLM
agentgateway
LangSmith
Langfuse
Languages, frameworks & APIs
Python
TypeScript
Node.js
Go
Rust
FastAPI
Django
Flask
Express.js
React
Next.js
Astro
Angular
REST APIs
GraphQL
gRPC
Databases & vector stores
PostgreSQL
MySQL
MongoDB
Neo4j
FalkorDB
pgvector
ChromaDB
Pinecone
Qdrant
Weaviate
Cloud
AWS
Google Cloud
Azure
Next step
Ready to take the first step?
Tell us about the problem. The first 30-minute conversation is free and carries no obligation.
Or email us at hello@giilab.in