OmniTensorLabs — AI Product Studio
The model is the easy part.
The hard part is the world model around it: a durable, event-sourced picture of a company or a life that an AI can reason over, with the evidence to show it’s right. That’s what we build, and ship as products.
Three products,
one conviction.
Memory, not chat.
Every product keeps an event-sourced world model and reasons over what is true now — not a transcript that vanishes when the tab closes. For OmniManas that world is a company; for Saathi, one person’s day.
Grounded, and accountable.
Every AI action is permissioned, explainable, and traceable to its evidence. When the answer isn’t known, the system says so — a judge that answers “unknown” beats a judge that guesses.
Evidence over adjectives.
We publish the numbers, including the unflattering ones. Multivon set itself a 50% determinacy bar, scored 20.9%, and shipped the result in public. Proof travels further than a superlative.
The products
Two worlds · one instrumentTwo world models — one of a company, one of a life — and the instrument that keeps them honest.
OmniManas
Company OS · B2B
Give your company one mind.
HR, projects, sales, support, and knowledge on one shared graph, with AI that works as a permissioned member of the team rather than a chatbot bolted onto the edge.
Saathi
Multimodal Personal Agent · Android
A companion that sees, hears, and remembers.
A Hindi-first, voice-first agent for elderly and low-vision users. It brings speech, camera, SMS, and notification signals into a private world model, then explains what it knows before it acts.
Multivon
Developer Tools · Open source
AI evaluation for teams that ship.
44 evaluators, one Python API, entirely local. Every score ships a confidence interval; every judge can answer “unknown.” The eval that tells you when a regression is real, not just a number that moved.
Saathi × Multivon
The product and the proof.
A multimodal agent is not useful because each model looks impressive in isolation. The whole loop has to work: perceive the right thing, remember it, choose the right action, and recover when reality is messy.
Saathi supplies the real-world tasks. Multivon turns their outcomes, traces, memories, and visual evidence into an explicit evaluation contract—so reliability can be measured before the agent reaches a family.
Recall a message or appointment
Resolve the right person, message, and date; preserve the source behind the answer.
Read a medicine label with the camera
Guide framing first, abstain on weak evidence, and never add a label fact that is not visible.
Interrupt or correct the assistant
Stop, repeat, or clarify without leaking into an unintended tool call or action.
Log and recall a blood-pressure reading
Return the exact, user-scoped value with its time—even after a restart.
Recover messages after going offline
Deliver every queued event once, suppress retries, and expose stale sync state.
Vision evaluators are experimental, and Saathi's field results will be published only after the on-device pilot. The contract comes before the score.
How we build.
OmniTensorLabs is a small studio with roots in applied AI research. We put that rigor into products people use every day.
The architecture is the opinion. Each product runs on an append-only event log and a model-agnostic reasoning layer — memory that survives a restart, an audit trail for every decision, and no lock-in to a single model provider. It is the unglamorous engineering that makes AI safe to put in front of a company’s data or a family’s day.
We ship what we would depend on ourselves. If it isn’t reliable enough to run our own company or hand to our own parents, it isn’t ready.
Let’s talk.
Partnerships, press, or curious about what we’re building? Write to us — we reply within a day.