Agent Orchestra is whatever you need it to be — code review, testing, fixing, triaging, documentation — a fleet of specialized agents powered by the best AI models from 8 providers, working together so your team ships faster.
Every PR gets a deep, context-aware review in seconds — catching bugs humans miss on their third cup of coffee.
Broken build? The Fixer agent patches, tests, and pushes the fix before you finish reading the error.
Generates and evolves test suites that actually cover edge cases — not just happy paths.
Docs that update themselves every time the code changes. Never stale, never wrong.
Issues get ranked, routed, and contextualized automatically. Kill your backlog grooming meetings.
Tag @bot in Slack with a mockup or a team discussion. Get structured design specs or backlog items — right in the thread.
Agents learn from every outcome — merge rates, review comments, failure patterns. Tomorrow's fix is informed by today's data.
Anthropic, OpenAI, xAI Grok, Google Gemini, Mistral, Groq, DeepSeek & more. The system picks the best model for each task — optimizing for cost, speed, and quality.
Define sprints as files in your repo. Agents pick up tasks, write code, run browser tests, fix failures, and open PRs. You review and merge.
Open a PR yourself? Agents auto-review with risk scoring, security scanning, and test results — posted as PR comments before your team looks at it.
Already using AI for code? Agent Orchestra doesn't replace your tools — it makes them actually deliver. Think of it as the operating system that turns individual AI actions into a coordinated pipeline.
Individual AI sessions are powerful but isolated. They don't persist context across your pipeline, don't learn from CI failures, and don't coordinate with your team's workflow.
Agent Orchestra fills every gap — persistent codebase memory, multi-agent coordination, and automated pipeline recovery. Your code gets reviewed, tested, documented, and deployed automatically.
Why pay premium rates for every task? Agent Orchestra automatically routes each job to the right model — fast and cheap for classification, powerful for architecture decisions, budget models for bulk analysis.
Anthropic, OpenAI, xAI Grok, Google Gemini, Mistral, Groq, DeepSeek, and Hugging Face — all behind one unified API, with cost tracking and circuit breaker failover built in.
@bot
in Slack. Get structured output.
Your team already discusses features, shares mockups, and debates architecture in Slack. Now those conversations automatically become actionable specs and backlog items.
Share a mockup screenshot in #design and tag the bot. It analyzes the image with vision AI and replies in-thread with:
Reply in the thread to refine — "focus on the nav bar" or "how does this look on mobile?"
Having a feature discussion in #team? Tag the bot to turn it into backlog items. It reads the full thread and replies with:
Asks clarifying questions in-thread before finalizing — like a real PM, not a form.
These aren't our numbers. They come from PwC, the NBER, METR, and Stack Overflow. The data is clear: AI adoption is sky-high, but actual results are in the gutter. We built Agent Orchestra to fix that.
We pass through AI compute at virtually no markup. As we scale, our costs drop — and so does your bill. That's it. No enterprise tax. No per-seat gotcha.
↓ Our cost drops → your cost drops. Aligned incentives, not extraction.
We're rolling out slowly and deliberately. Each org gets a single seat to start. Once you're in, you're in — and you'll be first in line as we expand.
Each agent is purpose-built for a stage of your pipeline. They coordinate, share context, and evolve together — choosing the right AI model for every task automatically.
Always on: Project Manager (Slack) • Incident Responder (production monitoring)
The backbone — ingestion, prioritization, and orchestration
The brain of the pipeline. Parses trigger context, clones repos, and executes every stage in the correct order with failure recovery.
/qa/reports/<date>-summary.md)
A developer opens a PR. The Orchestrator detects the
trigger, clones the branch, runs
Collector → Triager → Walker → Tester
→ Fixer → Reviewer → Documenter →
Accountant
in sequence. Within 10 minutes the PR has a full review
comment with risk score, test results, auto-generated docs,
and a cost breakdown — before anyone on the team even
looks at it.
Ingests signals from 15+ analytics platforms, CI results, and error trackers. Detects UX friction, regressions, and funnel drop-offs before a human files a ticket.
/tmp/signals.ndjson)
Collector pulls data from your GA4, Sentry, and Clarity
accounts overnight. It detects that 38% of users drop off at
step 3 of your onboarding flow, correlates it with a Sentry
JS error spike on that page, and flags a
ux_friction signal with severity
high. The Triager picks it up minutes later and
creates a prioritized ticket — complete with session
replay evidence.
Clusters raw signals by root cause using ML, deduplicates against your backlog, and scores every issue by impact. Writes prioritized tickets your team can act on immediately.
frequency × severity ×
log₂(affected_users+1) × recency ×
multi_source_boost
/backlog/open/
Triager receives 47 signals from last night’s
Collector run. It clusters them into 12 root causes,
deduplicates 4 against existing backlog items, and scores a
checkout crash at P0 (frequency: 200+, severity: critical,
1,400 affected users). A ready-to-act ticket lands in
/backlog/open/ before your standup starts.
Write, test, fix, and review — automatically
Maps every route via static analysis, walks them in a real browser, and auto-generates production-quality Playwright E2E tests. Supports React, Next.js, Vue, Angular, Svelte.
data-testid (preferred) → aria-role
→ CSS → LLM visual ID
waitForTimeout — always
explicit conditions
Walker scans your Next.js app and discovers 23 routes
including 4 auth-gated flows. It launches Playwright, walks
the full signup → onboarding → dashboard →
settings flow, records every interaction, and generates
signup-flow.spec.ts with proper
getByTestId() selectors. Next PR that touches
the signup page? Diff Detector re-walks only that flow in 90
seconds.
Auto-detects your test frameworks, runs all relevant tests, and classifies failures as genuinely broken, flaky, or chronically flaky. Clear reports for the Fixer.
/qa/reports/<date>-test-results.md)
flake-history.json)
Tester detects Jest (unit) + Playwright (E2E) in your repo.
It runs 342 unit tests and 23 E2E specs. Two unit tests
fail. It retries them — one passes on retry (marked
flaky), one fails consistently (marked
broken). The Fixer gets a clean target: fix the
real failure, flag the flaky test for investigation.
Automatically fixes issues within a strict safety scope. Lint issues auto-applied. Guarded fixes verified then reverted instantly if anything breaks. Business logic never touched.
Tester reports a broken import and a type error in two
files. Fixer classifies both as GUARDED, sends
the failing code + error context to Claude, receives
structured edits, applies them, re-runs the affected tests.
Both pass. Git patches are staged. If either had failed, the
fix would have been reverted and a ticket created instead.
Reviews all changes, classifies every file, computes a risk score (0–100), detects breaking changes, and generates a complete PR description with review checklist.
A PR touches 8 files: 2 API route handlers, 1 DB migration, and 5 tests. Reviewer classifies them, scores risk at 62 (high) due to the DB schema change, detects a removed export that would break 3 downstream consumers, and posts a PR comment: “High risk. DB migration + breaking API change. 3 affected workflows. Suggest human review before merge.”
Analyzes git diffs for correctness, style, security, and architectural impact. Produces structured findings with file/line references and a composite risk score.
Detects benchmark regressions using statistical significance and identifies resource bottlenecks across CPU, memory, I/O, and bundle size.
Manages the dependency lifecycle from staleness detection through safe update planning, with breaking change analysis and migration guides.
Learn, evolve, document, and design — continuously
A multi-agent product strategist. Spawns five advisor agents that debate priorities in a structured 4-round process. Produces a ranked, evidence-backed roadmap.
roadmap/direction.md
roadmap/roadmap.md)
Sunday 1 AM: Evolution Engine kicks off. The User Advocate flags a critical onboarding gap (38% drop-off). The Growth Analyst identifies a conversion opportunity. The Stability Guardian vetoes a new feature push — error rates are up 12%. After 4 rounds: P0: Stabilize error rates. P1: Fix onboarding drop-off. P2: Pricing page experiment. P3: Refactor hotspot module. All backed by data, all aligned with your vision file.
Auto-generates and maintains living documentation from source code. Updates on every PR. Detects stale docs by hashing source against doc references.
~$0.11–$0.31 per PR; ~$0.75–$1.50 for full nightly refresh
docs/ directory committed to your repo
A developer adds a new /api/v2/orders endpoint.
Documenter detects it, generates an API reference with
request/response schemas, updates the architecture diagram,
writes a changelog entry, and produces a review guide:
“Start with the route handler, then check the
service layer, then the migration.”
All committed to docs/ automatically.
Monitors UI for visual regressions, accessibility violations, and design system drift. Analyzes session replays and heatmaps to surface UX friction backed by real data.
A developer updates a shared Button component. Designer detects 14 pages are affected, runs screenshot diffs on each, catches that the mobile checkout button now overlaps the price label on screens under 375px. It also flags that the new button color fails WCAG AA contrast against the dark theme background. Both land as tickets — with before/after screenshots — before the PR is even reviewed.
Reduces time-to-first-commit for new team members by generating architecture overviews, setup guides, module deep-dives, and common workflow documentation.
Vulnerabilities, compliance, and regulatory enforcement
Scans every PR for OWASP Top 10 issues, dependency CVEs, secret leaks, and insecure configurations. LLM-powered contextual analysis reduces false positives.
A PR adds a new user search endpoint. Security Auditor
detects the query parameter is interpolated directly into a
database call — classic SQL injection (OWASP A03). It
also catches that a .env.local file with a
Stripe secret key was accidentally staged. The PR is flagged
CRITICAL: merge
blocked until both are resolved. The Fixer auto-remediates
the SQLi with parameterized queries; the secret is removed
from staging.
Ensures your codebase complies with regulatory frameworks. Scans for PII exposure, consent flow gaps, data retention violations, and license conflicts.
A developer adds logging to the checkout flow. Compliance
Officer detects that the log statement includes raw email
addresses and IP addresses — PII that violates your
GDPR data minimization policy. It also flags that a new npm
package uses a GPL-3.0 license, which conflicts with your
MIT-licensed project. Both violations are blocked with clear
remediation steps:
“Hash or redact PII before logging. Replace
gpl-package with MIT-compatible
alternative.”
Team coordination, incident response, and cost tracking
Lives in Slack as your always-on project coordinator. Tracks sprint progress, surfaces blockers, runs async standups, and keeps your team aligned without another meeting.
Monday 9 AM: PM Agent posts in #engineering:
“Sprint 14, Day 3. 8/21 points completed. 2 tickets
blocked — checkout refactor waiting on API review
(tagged @sarah), payment migration needs test data (tagged
@mike). Velocity trend: on track for 19/21 by Friday.
Suggested: move P3 dark-mode ticket to next sprint to
reduce risk.”
No standup meeting needed.
Monitors production in real-time. When error rates spike or services go down, it correlates alerts with recent deploys, identifies probable cause, and can auto-rollback.
3:17 AM: Error rate spikes from 0.1% to 4.8% on the
/api/checkout endpoint. Incident Responder
fires within 30 seconds. It correlates the spike with a
deploy at 3:12 AM (commit a3f7b2c), identifies
a null pointer in the new payment handler, triggers
auto-rollback, and posts to #incidents:
“P0: Checkout errors 48x baseline. Root cause: null
ref in payment handler. Auto-rolled back. Error rate
recovering.”
Pages on-call only if auto-rollback fails.
Every agent emits cost entries. The Accountant aggregates them into an append-only ledger, tracks per-run and per-tenant billing, and generates clear cost summaries.
Tonight’s nightly run: Collector used 12K tokens ($0.04), Walker ran 8 minutes of Playwright ($0.04), Fixer used multi-model debate with 45K tokens ($0.68), Documenter generated changelogs for 3 PRs ($0.33). Total run: $1.09. Accountant logs every line item, appends to the ledger, and your dashboard shows the cost breakdown by stage and by ticket.
Validates release readiness across all gates, generates changelogs from commit history, and assesses rollback risk for every release candidate.
Shipping fast. Here's what landed recently.
The entire industry is talking about cutting headcount. We think that's backwards. Your people have the domain knowledge, relationships, and judgment to build new revenue streams, scale the business, and reshape their own roles — if you stop burying them in maintenance work.
Agent Orchestra takes over the grunt work — the repetitive reviews, the boilerplate tests, the 3 AM build breaks — so your team can focus on what actually compounds: new products, new markets, and the kind of deep creative work that moves the dial on science and innovation.
The goal isn't fewer people. It's the same people doing work that was never possible before. Growing the business, not just maintaining it.
Drop your email. We'll let you know the moment your seat is ready.
No spam. No selling your data. Just early access.