The Multi-Agent Trust Stack — one model can’t check itself. Rivals can.
A single model is fast, polished, confident — and sometimes wrong. Ask it to check itself and you get a rephrased version of the first answer, not a second opinion. Decidi sets rival frontier models against each other, each trained independently, then puts the result through a separate Final QA audit — built to catch what survives when one confident model answers unchallenged.
Many minds. One signed-off result.
Decidi starts as an ordinary chat and escalates when the work earns it. The draft is contributed to and challenged by a committee of independent AI minds — up to six debaters, plus an impartial moderator and a Final QA audit that signs it off before it ever reaches you. Many minds catch what one confident model misses. What comes back is ready to plug straight into your workflow.
GPT, Claude, Gemini and Grok — plus expert personas — each add their own angle and evidence. Not one model’s narrow, confident take.
Every Multi-Agent verdict is reviewed, challenged and signed off by the proprietary Final QA audit before it reaches you, with its “verify this” list attached. Finished work, not a first draft.
Run a Multi-Agent Team from your own tools and AI agents via the Decidi API — work flows in, committee-signed output flows back out.
What each layer exists to catch
the mechanismNothing is challenged. Whatever the model got wrong ships with the same confidence as what it got right.
Disagreement surfaces. Where independently trained models split, an answer needs a closer look.
Assumptions are named. Unstated assumptions and missing evidence are listed, not glossed over.
The consensus is attacked. The strongest counter-case is argued on purpose, before you rely on the answer.
A cold read hunts fabrication. An auditor that took no part in the debate re-derives the numbers and strikes or flags any specific it cannot stand behind.
Human verification. Every citation, figure and factual claim worth confirming lands on the “verify before you rely on this” list — surfaced to you, never shipped silently.
No layer makes AI work infallible — each one widens what gets caught. That is the honest claim: not a promise of perfection, but a process where every answer is challenged, cross-checked and handed over with its open questions attached.
The Decidi workflow
Free chat on the lab you choose — GPT, Claude, Gemini or Grok — with a specialist sidekick reading over your shoulder, and any answer one tap from a challenge by a model from a rival lab.
Specialist minds on rival models take the work — to argue a decision out and return an audited verdict, or to divide the job and produce the finished deliverable. The five layers below are what happens inside that run.
- Creates the draft
- Performs the task
- Generates the first answer
- Checks facts
- Checks citations
- Fixes inconsistencies
- Lists assumptions
- Surfaces missing evidence
- Flags legal / commercial / technical risk
- Challenges the conclusion
- Argues the counter-case
- Pressure-tests confidence
- Cleans and formats
- Assigns a confidence level
- Signs off decision-ready work
What is the Final QA audit?
A separate, always-on verification pass that audits a synthesised verdict against known AI failure modes — hallucinations, weak reasoning, missed caveats — and attaches every flag it finds to the verdict: shown to you, never hidden. This is Decidi’s proprietary sign-off step, also called the Final QA layer or Final QA pass. More in the glossary →
Agreement is not proof. A model that reviews its own work returns a rephrased first answer; a rival trained by a different lab returns a real one.
What the stack catches
A decision tool lives or dies on honesty
The stack is the mechanism. This is the commitment behind it — what we hold ourselves to, and what we refuse to do even when it would look better.
- Show you where the models actually disagree — not a smoothed-over consensus.
- Name the assumptions the answer rests on, and the one that would flip it.
- End every verdict with a specific “verify before you rely on this” list.
- Tell you plainly when a decision needs a qualified professional in your jurisdiction.
- Be upfront about what we don’t have yet — no SOC 2, early-stage, said out loud.
- Let invention pass unchallenged. Rival labs’ models cross-check the claims, catching fabrication is the Final QA audit’s job — a citation, statute, number or date it cannot stand behind is struck or flagged — and anything unverifiable is surfaced for your verification.
- Fake certainty, testimonials, ratings or customer counts.
- Pretend the output is infallible or a substitute for professional advice.
- Use your work to train AI models.
- Bury the risks to sound more confident than we honestly are.
The answer was never less AI. It’s AI that answers to someone.
For the work and decisions where being wrong is expensive, one fast, confident model isn’t enough — but avoiding AI isn’t the edge anymore either. Decidi is how you use AI the right way: a committee that drafts, challenges and signs off, so what you act on has been argued against before you rely on it. Agentic runs fail quietly — a step invented, a failed tool call treated as data, the objective drifting at every hand-off. This is the layer built to catch that.
Start in chat