Beta Connect Next is under active development. Answers and features may change or break.

For developers & AI power users

Don't trust one model.
Get the answer three of them agree on.

GPT, Claude, and Grok draft independently, debate on evidence, and converge on one answer you can verify — not one model's confident guess.

Free to try · Pro is $4.99/mo — bring your own keys, no token markup

OpenAI Claude Gemini Grok DeepSeek The Council draft · debate · verify Verified Answer
Five providers → one council → one verified answer
86.4%
win rate vs. single model
+45pp
accuracy lift (hard sets)
3+
models deliberating
0
markup on your tokens

How it works

One model can be confidently wrong. A council checks itself.

Instead of one black box, your question goes to several models that work like a panel of experts — independently, then together.

01

Draft independently

Each model answers on its own, with no peer anchoring. Different strengths surface different angles — diversity is the asset.

02

Debate on evidence

The models see each other's answers and challenge the reasoning. Only points backed by a recomputation, counterexample, or citation survive.

03

Synthesize & verify

The strongest, validity-checked answer is assembled — disagreements resolved on merit, not on whichever model sounds most confident.

"Is optimistic or pessimistic locking better?"
GPT-5
Claude
Grok
✎ drafting independently — no model sees another ⚖ debating on evidence — 1 dispute resolved ✓ one verified answer

What you get

Built to reason, not just respond.

Four ways to orchestrate

Auto picks the effort. Council merges independent answers. Debate makes the models argue it out. Compare shows all three side by side.

See the reasoning

Watch the council draft, debate, and converge live — with verdict chips showing what was verified, disputed, or revised.

Bring your own keys

On Pro you connect your own provider keys and pay them directly. We never mark up your tokens.

Benchmarked, not claimed

Measured on GPQA, MMLU-Pro and GSM8K against each model alone — the numbers are public.

The proof

86.4%
win rate against the best single model

On hard reasoning sets, orchestration recovered answers that every individual model got wrong. See the full methodology and per-category results.

See full benchmark →