AI development: agents and LLM apps that hold up in production
We design and ship LLM applications, retrieval systems and tool-using agents that answer from your own data. Every build starts with an evaluation set, so quality is measured rather than guessed.
What we deliver
Scoped in the 48-hour proposal, priced as a fixed quote or a monthly team.
Use-case scoping
We pick the workflows where a model earns its cost, and write down what a wrong answer would cost you.
RAG knowledge assistant
Retrieval over your documents, tickets or database, with citations, access controls and a clear fallback when the answer is not in the source material.
Tool-using AI agents
Agents that call your APIs and read your systems, and hand off to a person at defined checkpoints rather than running open-ended loops.
Evaluation harness
A versioned test set and scoring pipeline, so every prompt or model change is checked before it reaches users.
Guardrails and safety
Input and output filters, personal data redaction, rate limits and refusal rules tuned to your domain and compliance needs.
Model routing and cost control
Routing between hosted and open-weight models by task, with token budgets, caching and per-feature cost reporting.
Production monitoring
Traces, latency and quality dashboards, with alerts when answer quality drifts after a model update.
How we run ai & agents projects
- 01
Reply in 4 hours
We reply within 4 hours during IST business hours and book a scoping call for the next working day.
- 02
Proposal in 48 hours
You receive scope, architecture, model choice, timeline and a fixed quote for the first phase.
- 03
Clickable prototype in 7 days
A working prototype answers real questions from your data, so answer quality can be judged early.
- 04
Two-week sprints
Each sprint adds retrieval, agent steps or evaluation coverage, and ends in a live demo you can test yourself.
- 05
Weekly releases
Changes reach production each week through CI/CD, with evaluation results attached to every release.
Stack
Chosen per project. See the full stack.
- Claude API
- OpenAI API
- Google Gemini API
- Llama
- Mistral
- LangGraph
- LlamaIndex
- pgvector
- Pinecone
- Langfuse
- Promptfoo
- FastAPI
- Python
- Ollama
What you can expect
- Answers that cite the source document they came from, so your staff can check them quickly.
- A measured quality baseline before launch, and a regression check on every later change.
- Clear running cost per feature, so model spend can be tracked and capped.
- Human handoff paths for the cases an agent should not decide alone.
AI & Agents by city
Questions buyers ask us
Something else? Ask us directly. First reply within 4 hours.
Which AI models do you work with?
We work with the Claude, OpenAI and Gemini APIs, and with open-weight models such as Llama and Mistral that can be hosted in your own cloud region. The choice depends on data residency, latency and cost, and we set out the trade-off in the proposal.
How much does an AI project cost?
It depends on scope, the number of data sources and how strict the evaluation needs to be. We give a fixed quote within 48 hours of a short scoping call, so you know the cost before you commit.
Can you build an assistant on our own documents?
Yes. We index your documents with access controls that mirror your existing permissions, so an employee only receives answers drawn from files they are allowed to open. We also test whether the assistant admits when the answer is not in the documents.
Do you build AI systems for businesses in India?
Yes. Our engineering team is based in Thrissur, Kerala, and we host data in Indian cloud regions where a client needs it. Indian languages such as Malayalam, Hindi and Tamil can be included in the evaluation set alongside English.
How do you stop an AI system from making things up?
We cannot promise zero errors, so we limit what the system is allowed to answer, require citations for factual claims, and measure error rates on a test set before launch. Anything outside the approved scope is refused or passed to a person.
Tell us what you need shipped.
Send a short brief. You get a written proposal with scope, stack, timeline and a fixed price within 48 hours.