Who reviews
the AI?
DeepParallel is a coding agent that doesn't trust a single model. An independent Guardian reviews every edit before it lands, and a panel deliberates on the hard calls. Many models, one verdict.
or pipx install deepparallel · then run deepparallel or dp
$ dp run "add a withdraw() method to account.py" ◆ I'll add withdraw() with a balance check. › edit_file account.py ┌─ diff ───────────────────────────────────── + def withdraw(self, amount): + self.balance -= amount └────────────────────────────────────────────── guardian › a second model is reviewing the diff… ✗ BLOCKED bug: no guard for amount > balance (overdraft) or amount ≤ 0 apply anyway? [y/N] ▋
the mechanism
A second model, on every edit
Single-model agents grade their own homework — same model, same blind spots. DeepParallel routes every change through an independent reviewer before it touches your files.
The agent writes
It reasons, calls tools, and proposes a diff — like any modern coding agent.
A different model reviews
An independent model inspects the diff and returns safe / risky / bug, with a reason — before anything is written.
Apply with a verdict
You approve with a second opinion attached. In CI, dp review exits non-zero to block the bad ones.
--deep
For the hard calls, convene a panel
Run several models in parallel and let a judge synthesize one answer — with a consensus score, and the dissent surfaced when they disagree.
what you get
A full agent, plus a conscience
Review before apply
An independent model reviews every diff and returns a verdict with a reason. You approve knowing a second model checked it.
--deep deliberation
N models answer in parallel; a judge synthesizes the best one and scores how much they agreed.
14 native tools
Read, edit, glob, grep, shell, sandboxed execution, tree-sitter AST edits, web fetch & search, and vision — gated and streamed.
dp review in CI
A pre-commit hook or pipeline step that exits non-zero on a risky or buggy diff. An independent model gates your AI code.
Switchable strategy
reason→answer, escalate-on-uncertainty, dual compare — change the model strategy live, per turn.
Your own fleet
Runs on a Crowe-owned model stack, not one external vendor — for teams that can't ship code to a public API.
research · conduit
Why parallel models help: pass the thought, not the word
Agents that collaborate through text squeeze a continuous thought through one emitted word each hand-off. Conduit is our study of relaying the hidden state directly. On real open-weight models the latent channel recovers far more of the meaning than the word the model would have said.
pricing
Free to start. Pay for the panel.
The single-model agent and every tool are free, forever. The cross-model layer — Guardian, the council, fusion — is the paid value.
- Full single-model agent
- All 14 tools
- Streaming + gated edits
- Bring your own key
- Everything in Free
- Guardian edit review
- Fusion modes
- --deep council + consensus
- Hosted inference, no keys
- Everything in Pro
- dp review PR-gate
- Cross-model review reports
- Shared config + billing
- Priority support