Vāda

Multi-model deliberation

The room outperforms the individual.

Bring a question. A team of AI models debates it. You get the disagreement, not just the answer.

AN ATTĀ PRODUCT
Strategist
Critic
Devil's Advocate
Synthesizer
Researcher
Operator
01 / What It Is

You bring a question.A room deliberates.

Vāda runs a team of AI models on your question. Each model reasons independently. Each sees what the others said. You get the full deliberation — the disagreements, the convergence, the synthesis. Not one answer. A room's verdict.

01

You submit a question.

02

Each model reasons independently.

03

Models read each other and respond.

04

A synthesizer reconciles their positions.

05

You receive the verdict and the full transcript.

02 / Why It Works

Disagreementis the signal.

A single model cannot see its own blind spots. When models disagree, that disagreement is information — it marks the genuine uncertainty in the question. Vāda surfaces that. You learn not just what the models think, but where they diverge and why.

One model gives you its best guess. A room gives you the shape of the problem.

Single model

Returns a confident answer. Blind spots are invisible. You cannot tell what it missed.

vs
Room of models

Disagreement is explicit. Convergence is earned. You see exactly where confidence is real.

04 / What This Is Not

Vāda is not a chatbot.

No memory. No personality. No ongoing relationship. A fresh room for every question.

Vāda is not a workflow.

No steps. No pipelines. No automation. Deliberation, not execution.

Vāda is not a search engine.

It does not retrieve answers. It produces judgment on the question you bring.

Vāda is not trying to be helpful.

It is trying to be right.

Input
Your question. The decision you're stuck on.
Reviewers · independent analysis
Cross-critique · response
Audit & revise
optional
Some teams add an audit gate. If the conclusion fails review, the team revises.
Conclusion
+ transcript
  • Structured recommendation
  • Convergence and dissent, named
  • What was assumed and what remains open
02 / How It Works

Deep thinking, on demand.

You bring a question. Vāda launches a team of agents on it — reviewers running across multiple models, working through the question under a structured protocol. No single model's blind spots. No one viewpoint deciding for you.

The shape of the work is defined by the team you launch. A team can be a panel of independent reviewers — each on a different model — returning their analysis. Or a deeper engagement with multiple rounds, cross-critique, an audit gate, and a revision loop. You pick the team that fits the decision.

Whatever the team's shape, the deliverable is the same: a structured conclusion with the full transcript attached. Every reviewer's reasoning, preserved. Auditable. Defensible to anyone who later asks how the decision was reached.

The question you walked in with is not always the question you walk out with. That clarity is what you came for.

03 / Try It

Bring a question.

A room of AI models will deliberate on it. You get the full transcript — the disagreement, the convergence, the verdict.

04 / For Developers

Use Vāda from any AI assistant.

Vāda exposes a hosted MCP server. Connect it to Claude, Cursor, or any MCP-compatible client. Your AI assistant can run Vāda deliberations as a tool call.

Tool call example

vada__deliberate

question: "Should we expand to Europe now?"

spec_id: "vada-reviewers-synthesis"

Returns: full deliberation transcript + synthesized verdict