Now in private beta

The bottleneck isn't writing the code. 
It's deciding what to build. 

Maven stress-tests your engineering decisions with multi-agent adversarial debate — grounded in your own data. 3 minutes instead of a 3-day meeting.

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STRESS-TESTDEBATEVALIDATEDECIDEAUDITVERIFYCHALLENGE

The problem

AI made building 10x faster. 
Bad decisions now ship 10x faster too. 

The decisions behind the code still move at the speed of a Slack thread and a 30-minute meeting. Every hour of decision delay now wastes ten engineers instead of one.

Before AI

Writing codeBottleneck
Deciding what to buildManageable

After AI (today)

Writing codeSolved by AI
Deciding what to buildNew bottleneck

When bad decisions ship at machine speed

$5.4B2024

CrowdStrike

One assumption, never challenged.

4 global outages2025

Cloudflare

Assumptions nobody inspected.

Hard down2024

Atlassian

Capacity assumption never revisited.

In every disaster post-mortem, somebody knew. Somebody had the objection. And somebody did not say it.

The solution

A second opinion before surgery. 
For your architecture. 

Maven sits between “we've decided” and “we've built it.” It breaks every decision apart into claims, assumptions, and risks — then stress-tests each piece against real data from your own systems.

01

Extract Evidence

Pulls real context from 7 enterprise sources — GitHub, AWS, Slack, Notion, past architecture decisions, your database, and org structure.

Grounded in reality, not hallucination.

02

Adversarial Debate

7 specialized AI agents challenge every claim. A Proposer builds. A Challenger attacks. A Devil’s Advocate stress-tests catastrophic scenarios.

Unflinching dissent by design.

03

Epistemic Verdict

A structured audit: what can be asserted with evidence, what cannot, what risks remain. Clear certainty classification with explicit constraints.

Not a recommendation — an honest assessment.

The Comparison

One request. 
Three very different answers. 

The same architecture prompt, handed to three different reviewers. Here's what comes back — and what Maven catches that the others don't.

Engineer Request
“Design a cross-region distributed caching layer for our user sessions.”
P95 < 50msMulti-regionRead-heavyHIPAA-scoped
Manual Review
Status quo

Architecture Review Board

2–3weeks
  • Depends on who happens to be free that week.
  • Slows shipping to committee cadence.
  • Edge cases surface only if someone remembers them.
Verdict · Bottleneck
AI Chatbot
Confident guess

ChatGPT / Claude / Copilot

0seconds
  • Dumps 500 lines of Redis config before asking a question.
  • Hallucinates consensus. Ignores split-brain risk entirely.
  • Violates your P95 latency SLA without knowing it exists.
Verdict · High Risk
Maven
Decision Gate

Adversarial debate + live evidence

0minutes
GitHubProd telemetryPrior ADRs
  • Red-teams the design with adversarial agents.
  • Cross-checks against your live cloud signals + ADRs.
Identified risk

“Cross-region sync cannot meet the 50ms P95 found in Prod DB telemetry.”

Approved scope

“Safe for single-region. Cross-region requires a formal CAP tradeoff.”

Verdict · Scoped & cited
What matters
Manual
AI Chatbot
Maven
Grounded in your telemetry
Challenges its own answer
Cites the evidence
Catches split-brain edge cases
Ships a verdict in minutes

When Maven isn't the answer: one-file bug fixes, stylistic code review, throwaway prototypes. We're the layer between “we decided” and “we shipped.”

Try a real decision

How it works

From question to verdict 
in under 3 minutes. 

01

Describe your decision

Tell Maven what you're planning in plain English. "Design a rate limiter" or "Should we migrate from Postgres to DynamoDB?"

02

Evidence is extracted

Maven pulls real context from GitHub, AWS metrics, Slack threads, Notion docs, past architecture decisions, and production databases.

03

7 agents debate adversarially

A Proposer builds solutions. A Challenger finds flaws. A Devil's Advocate tests catastrophic scenarios. An Evidence Verifier validates every claim.

04

You get an epistemic verdict

Not a vague recommendation — a structured audit. What can be asserted with evidence, what cannot, what risks remain, and explicit constraints for safe deployment.

The agents

7 agents. Zero groupthink. 

Each agent has a specific role, specific permissions, and uses a different LLM — so no single model's blind spots dominate.

GPT-4o

Proposer

Generates solutions, claims, and assumptions to kickstart the debate

Claude Sonnet

Challenger

Attacks weak claims, finds contradictions, and demands evidence

Llama 3.3 70B

Devil’s Advocate

Stress-tests assumptions and explores catastrophic failure scenarios

DeepSeek-v3

Evidence Verifier

Validates every claim against real production data and tool outputs

GPT-4o

Alt Generator

Creates alternative approaches and reframes the problem space

DeepSeek-v3

Integrator

Merges the strongest ideas, resolves conflicts between approaches

Process Judge

Monitors debate health, detects degeneration and circular arguments

DeepSeek-v3

Permission-controlled state machine

Every turn is a structured transaction. Only the Evidence Verifier can add validated constraints. The Reducer enforces invariants.

Product preview

See Maven think. 

Explore a real decision getting stress-tested — from evidence extraction through adversarial debate to epistemic verdict.

app.usemaven.dev/review/DEC-2026-042
ScopedDEC-2026-042

Add audit logs to payment database

12 debate turns · 8 claims validated · 3 constraints added

Can be asserted
  • Append-only log preserves audit trail integrity
  • WAL-based replication meets RPO < 1s
  • Read replicas handle audit query load
Cannot be asserted
  • Write performance under 10K+ TPS concurrent audit inserts
  • Cross-region consistency for distributed audit trail

Institutional memory

Maven remembers everything. 

Every decision. Every assumption that turned out wrong. Every trap that caught someone six months ago. The memory compounds.

ADW

Active Debate Window

Live working memory for the current debate

TSRB

Task Replay Buffer

Frozen snapshots from previous epochs

TDC

Distilled Context

Compressed insights across epochs

GDM

Global Memory

Cross-task intelligence that compounds

Knowledge doesn’t walk out the door

When your best engineer leaves, their reasoning stays. Every lesson captured, structured, and searchable.

Decision quality compounds

Your 100th decision is better than your first. Maven catches risks in seconds that used to take hours.

Patterns flow into future debates

Failure patterns, effective strategies, known traps — extracted and injected via embeddings.

The missing layer

Every tool makes you faster. 
None help you decide. 

PagerDuty
Tells you when it breaks
CodeRabbit
Reviews the code
Cursor / Copilot
Writes the code
MavenNew
Decides what to build
Jira / Linear
Tracks what to build

Use cases

Not just for software. 

Anywhere a team says “we have decided to...” and the cost of being wrong is real money.

Architecture Decisions

“Should we migrate to microservices?”

Vendor Migrations

“Is switching from Postgres to DynamoDB safe?”

Pricing Changes

“What breaks if we move to usage-based pricing?”

Hiring Plans

“Do we need a platform team or can infra scale?”

Market Entry

“Are we ready to expand to EU with GDPR?”

Compliance

“Does our auth flow meet SOC 2 requirements?”

Compliance

“Does our auth flow meet SOC 2 requirements?”

Market Entry

“Are we ready to expand to EU with GDPR?”

Hiring Plans

“Do we need a platform team or can infra scale?”

Pricing Changes

“What breaks if we move to usage-based pricing?”

Vendor Migrations

“Is switching from Postgres to DynamoDB safe?”

Architecture Decisions

“Should we migrate to microservices?”

Slow human decisions are the 
last un-automated bottleneck. 

We're working with early design partners to shape the product. If your team makes consequential decisions, we want to talk.