AI that reaches production, not just the demo.
We design, build, and ship AI systems for mid-market teams — production RAG, private fine-tuned models, and LLM features inside your product. Deployed in your cloud, measured with real evals, owned by your team.
Vychara — from Sanskrit vichāra: deliberate inquiry. We diagnose before we build, so you don't pay to find out AI was the wrong tool.
Three ways in, one standard of work.
Most engagements start small — an audit or a pilot — and grow into a build once the value is proven. Wherever you enter, you get senior hands on the problem and software your team can actually maintain.
Audits & Roadmaps
Know exactly what to build, and what it's worth, before you spend on a build.
- AI Readiness Audit & Roadmap — systems and data mapped, opportunities ranked by payoff and feasibility.
- LLM Cost & Quality Audit — evals, cost per query, latency, and the specific fixes to reclaim wasted inference spend.
- Technical due diligence — a straight read on an AI system, team, or vendor.
Systems & Products
The core work: AI that runs in production and survives contact with real users and data.
- Production RAG systems — ingestion, retrieval tuning, evals, guardrails, deploy.
- Private fine-tuned models — open models tuned and aligned to your task, in your VPC.
- LLM features in your product — copilots, semantic search, summarization.
- Agentic workflow automation — intake, triage, and document processing.
Training & Support
So the capability stays with your team long after we hand off.
- Team training workshops — hands-on RAG-in-production and fine-tuning, on your stack.
- AI Ops & maintenance — eval monitoring, drift, cost optimization, model updates.
- Fractional AI lead — senior direction without a full-time hire.
A short path from problem to shipped.
No long procurement cycles or bloated statements of work. We diagnose fast, scope tightly, and keep you informed every week.
Intro call
A focused conversation about what you're building and where it's stuck. By the end we both know if there's a fit — and if there isn't, we'll say so.
Scope & proposal
We confirm the problem in writing, then send clear options with a recommendation — fixed scope, fixed price, defined milestones. Usually within 48 hours.
Build
Senior engineering on the problem, evals throughout, and a written status update every week — without you having to ask.
Handoff & support
Documentation, a working system, and a team trained to run it. Ongoing AI ops available when you want it.
No prices on this page on purpose. Every engagement is scoped to your problem — we'll give you a clear number after the intro call, tied to exactly what you need.
Depth most AI consultancies don't have.
Plenty of firms can call an API. Fewer understand what happens underneath it — and that difference shows up in your cost, latency, and quality.
Below the API line
We've pretrained language models from scratch — tokenizer to alignment. You almost certainly don't need one built that way, but knowing how the machine works is the difference between tuning a system and guessing at it.
Product and ML under one roof
A decade-plus of shipping production web applications in big tech means we build the ML and the product around it — which is usually where these projects stall.
Private by default
Fine-tuned open models deployed in your cloud. Your data never leaves your walls, and inference often costs a fraction of frontier APIs on your specific task.
Evals before opinions
Every recommendation comes with a measurement. If a claim can't be measured, we'll tell you that too — including when AI is the wrong tool for the job.
Tell us what you're trying to ship.
Bring the problem and where it's stuck. In one call you'll get a straight read on whether AI is the right move, what it would take, and how we'd approach it. If we're not the right fit, we'll point you somewhere better.
Book an intro call →