Most AI prototypes never reach production. The ones that do usually arrive late, expensive, and fragile. We build the other kind — systems with evals, guardrails, cost controls, and a clear story about what they do and don't do well.
Chatbots, autonomous agents, RAG, copilots, fine-tuned models, edge inference. Scoping to eval to deploy.
Each is a full discipline — architecture, evals, cost modeling, monitoring. We've shipped all six across a dozen industries.
Your support handles 10K+ queries daily without adding staff. Customers get instant answers 24/7.
Learn more →Your team reclaims 10+ hours weekly. Routine tasks complete overnight while you sleep.
Learn more →Your knowledge base answers accurately with sources. No hallucinations, no made-up facts.
Learn more →Your team's productivity multiplies. Repetitive work automates while humans focus on strategy.
Learn more →Your AI speaks your industry's language. Get accuracy that generic models can't match.
Learn more →Zero latency, complete privacy. Your data never leaves your infrastructure.
Learn more →We pin down the use case, the success metric, the eval dataset, and the guardrails — before a line of code is written. Most AI projects fail here, not in the build.
A working end-to-end prototype in 1–3 weeks. Real data, real LLM calls, real answers. You test with actual users before we commit to production architecture.
Eval dataset, regression tests in CI, human-in-loop review flow. If we can't measure whether it got better, we don't ship it.
Production deploy with observability, cost controls, prompt versioning, drift monitoring. You own the stack and the weights — no vendor lock-in.
Monthly eval review, prompt tuning, cost optimization. Most GenAI systems degrade without care. Ours get better.
If you can't grade it, you can't ship it. Every system we build has an eval harness from day one.
We start with the smallest model that works, then upgrade only where accuracy demands it. Your token bill stays predictable.
Most use cases are better served by retrieval. Fine-tuning is a scalpel, not a hammer — we use it when the numbers actually justify it.
PII redaction, prompt-injection defense, rate limiting, fallback paths. Production AI needs production discipline.
No proprietary platforms. We build on OpenAI / Anthropic / open models, with infra you can swap out. If we part ways tomorrow, your system keeps running.
We'd rather show you an accuracy delta than a pitch deck. Every project has baseline metrics, lift numbers, and a cost model.
A complete cattle management system for a real working gaushala in Coimbatore — tracking every cow, every milking, every medical treatment, every breeding cycle, every birth — across two apps that share one brain: a desktop version for the office and a mobile-friendly version that the workers carry around the shed in their pockets.
B2B competitive intelligence consultancyAn AI chatbot platform built for Prodzen — a competitive intelligence consultancy — that turns their long competitor research reports into chat bots prospects can actually talk to, with built-in lead capture so every conversation becomes a qualified sales lead.
Wholesale / retail tradingA receivables and payables system for J.A Paramanantham & Bros — the wholesale shop's complete who-owes-whom dashboard, with WhatsApp reminders sent from the shop's own business number, NEFT bank-payment file generation for paying vendors in bulk, and full ledger tracking down to the last invoice.
Wholesale / retail tradingA mobile stock-counting app for a wholesale shop in Tamil Nadu — built so workers can walk through the godown, count items in their hands, and log them in seconds, in either Tamil or English. Used every morning at J.A Paramanantham & Bros, a real Tamil Nadu wholesale business.
Bring us the use case. We'll give you back a scoped plan, an eval strategy, and a realistic cost model. No slideware.
Let's talk