Anvaya is an AI-powered enterprise assistant that turns scattered organisational data, knowledge, and tools into a single conversational interface — so people ask in plain language and get answers drawn from the right sources, with execution where it is authorised.
Ask in plain language. Get answers from your actual systems.
Anvaya sits across the databases, knowledge, and tools your organisation already runs — and answers from there, instead of asking people to learn where everything lives or how each system works.
Enterprise knowledge kept breaking the same way, so we built one front door.
In large organisations the information exists but the paths to it do not. A business figure lives in a database, the policy in a document, the procedure in a thread, and the person who knows is unreachable. Every question became a small investigation across systems nobody fully maps.
We built Anvaya to collapse that distance: one conversational interface that finds where the answer lives, retrieves across connected sources, executes authorised operations, and reasons across the pieces before returning a single contextual reply — held to the access rules and structure the enterprise already trusts.
What did we commit to in the March renewal?
Anvaya queries the contract source directly and returns the commitment with the exact figure and version in force — not a document somebody half-remembers.
How are we tracking against the logistics target this week?
It pulls the current numbers from the operational database, compares across the records you are permitted to see, and explains the trend instead of dumping a table.
Can we open a ticket for this without switching tools?
Where it is authorised, Anvaya runs the operation itself — creating the record and confirming it — so the conversation becomes the action, not just the query.
Anvaya retrieves across the databases, knowledge sources, and tools your organisation connects — and executes approved operations — rather than answering from a static index. The interface meets the data where it already lives.
A multi-tenant architecture with granular, role-based permissions means people only receive the capabilities and information their role permits. Executives, managers, and operators get progressively scoped boundaries — control by design, not by hope.
The intelligence layer stays configurable: your organisation chooses the provider and model that fit cost, capability, and policy. Sources, permissions, and workflows stay consistent as models change underneath.
Built as a PWA on your infrastructure or a private tenant. No conversation history is persisted by default, retention stays under your control, and nothing trains anyone else's models.
“It is the start of the day. An ops lead needs a figure that lives in a database three systems away and a policy nobody can locate. That recurring half-hour of hunting — across dashboards, docs, and the one colleague who knows — is what Anvaya removes.”
Organisations from a few hundred to several thousand feel it first: operations leads, support desks, and anyone whose job is answering questions that span systems. If finding the answer still means knowing where to look, Anvaya pays for itself quickly — and quietly.
Search returns documents and leaves the synthesis to you. Anvaya breaks a question into steps, retrieves across sources, queries authorised data, and returns one answered, contextual result — and can act on it where permitted.
Your infrastructure or a private tenant we provision together. Conversation history is not persisted by default, retention is configurable, and nothing is used to train external models.
Access follows your existing hierarchy through multi-tenant, role-based permissions. Each user only receives the information and capabilities their role allows, configured per deployment.
No. The model and provider are configurable, so the system adapts as models, costs, and capabilities change while your sources and permissions stay put.
Start with the demo, or send us the hardest question your team answered badly last week.