Your Autonomous Engineering Team..
Haiku for triage, Sonnet for code, Opus for reasoning — the right model for each task.
How It Works
From task to deployed code in 3 steps.
Describe Your Task
Tell the agent what you need in plain language via Slack, Teams, or CLI. "Fix the timeout bug in order-service" or "Add a health check endpoint."
Agents Execute the Lifecycle
The Supervisor routes your task to the right agents. They diagnose, write code, open a PR, run tests, and prepare for deployment — all autonomously.
Approve at the Gate
You review the PR, click Approve, and watch the agent deploy and validate. If anything fails, automatic rollback kicks in. You stay in control.
Verified Deliverables
See what your new workforce produces.
Auto-generated by Code Agent. Merged after human approval.
Diagnosed by Support Agent (Opus). Fix delegated to Code Agent.
Deployed by DevOps Agent. Health validated automatically.
The Agent Team
5 specialized agents powered by Claude — each routed to Haiku, Sonnet, or Opus for the right cost-latency tradeoff.
Supervisor Agent
Intelligent Task Orchestration
Receives tasks from Slack, Teams, or CLI. Classifies intent, routes to the right specialist, aggregates results, and coordinates rollback on failure.
- Intent Classification & Routing
- Multi-Agent Coordination
- Severity-Based Notifications
Support Agent
Read-Only Diagnostics
Investigates incidents across logs, traces, metrics, and commit history. Identifies root cause using deep reasoning and delegates the fix — never modifies production.
- CloudWatch & X-Ray Correlation
- Root Cause Analysis (Opus)
- Episodic Memory — Learns from Past Incidents
Code Agent
Full PR Lifecycle
Branches, reads your codebase, generates or modifies code, lints, commits, opens a PR, responds to reviews, and merges — only after a human clicks Approve.
- Atomic Multi-File Commits
- Human-in-the-Loop PR Approval
- SKILL.md Coding Standards Discovery
DevOps Agent
Deploy, Validate, Rollback
Runs Terraform, triggers CI/CD pipelines, provisions infrastructure, validates health post-deploy, and auto-rolls back on failure.
- Terraform Plan & Apply (Dev)
- Post-Deploy Health Monitoring
- Automatic Rollback on Failure
Test Agent
Automated Quality Gate
Executes the full test pyramid — unit, integration, and e2e — in CI sandboxes. Reports coverage, flags regressions, and blocks deploys on failure.
- Unit → Integration → E2E Pipeline
- Coverage & Regression Detection
- Post-Deploy Smoke Tests
Watch Your Agents Think
Real-time visibility into every decision, every tool call, every reasoning step.
No black box. Full transparency.
Earn Trust Gradually
Agents prove themselves before touching anything. Three modes, you control the pace.
Shadow Mode
Agents observe your environment and show what they would do — without executing anything. You rate their proposals. They learn.
Propose Mode
Agents draft actions and wait for your approval on every step. You click Approve or Reject. Nothing happens without your sign-off.
Active Mode
Agents execute autonomously, pausing only at critical gates (PR merge, production deploy). Full speed, full audit trail, human override always available.
Works With Your Stack
One config file per client. Zero hardcoded assumptions.
Git
Cloud
CI/CD
Deploy
Plus: Slack, Teams, PagerDuty, Jira, Linear, PostgreSQL, BigQuery, Snowflake, and more.
Not ready for the full platform? Start with a focused Claude service.
Fixed-scope, fixed-price engagements for teams onboarding to Claude, building custom agents, or optimizing what they already have.
Claude Jumpstart
Onboard your team to Claude in one week.
Custom Managed Agents
Bespoke agents for your workflows — not just engineering.
MCP Server Development
Connect Claude to your internal systems.
Claude Cost Audit
Cut your Claude spend 40–70% without losing quality.
Built on Claude.
CodeTractor is a Claude-native platform. We use Anthropic's Claude model family — Haiku, Sonnet, and Opus — to power every agent decision, with intelligent routing that picks the right model for each task.
Claude Haiku 4.5
Triage & Classification
Classifies incoming tasks from Slack, Teams, or CLI. Routes to the right specialist agent in under half a second.
- Intent detection
- Ticket triage
- Log parsing
- Structured extraction
Claude Sonnet 4.6
Code & Execution
Writes production code, opens PRs, runs tests, and drives deployments. The workhorse behind most agent actions.
- Code generation
- Refactoring
- Test authoring
- Tool use
Claude Opus 4.7
Reasoning & Root Cause
Deep reasoning for incident diagnosis, architecture decisions, and multi-step debugging. The model we reach for when stakes are highest.
- Root cause analysis
- Architecture review
- Incident diagnosis
- Migration planning
Haiku classifies → Sonnet executes → Opus reasons when stuck
CodeTractor vs. raw Claude API
Claude is the engine. CodeTractor is the platform around it.
| Feature | Raw Claude API | CodeTractor |
|---|---|---|
| Claude model family | You choose one model per call | Auto-routes Haiku → Sonnet → Opus |
| Multi-agent orchestration | You build it | 5 pre-built specialists, Supervisor included |
| Human-in-the-loop gates | You build it | PR approval, deploy gates, Slack/Teams built in |
| Episodic memory | Stateless | Agents learn from past incidents across sessions |
| SKILL.md capability discovery | N/A | Drop-in runbooks, no redeployment |
| Auto-rollback on failure | N/A | DevOps Agent reverts and alerts automatically |
| Cost optimization | Manual | 60–70% lower via routing + caching |
| Deployment target | Anthropic API | Your VPC, Bedrock, or Claude Managed Agents |
Frequently Asked Questions
What AI models power the platform?
Anthropic’s Claude family with intelligent model routing: Haiku for fast task classification, Sonnet for code generation and deployments, Opus for deep reasoning and root cause analysis. This reduces costs 60-70% compared to using a single large model for everything.
Can this run in our own infrastructure?
Yes. Two deployment options: Enterprise Self-Hosted (your VPC on AWS, GCP, or Azure using LangGraph + Bedrock AgentCore) or Claude Managed Agents (Anthropic-hosted SaaS, onboard in ~15 minutes). Your data stays where you choose.
How does human-in-the-loop work?
Code Agent opens a PR and pauses. A human engineer reviews via Slack or Teams and clicks Approve. Only then does the agent merge and trigger deployment. You stay in control at the gates that matter.
What happens if a deployment fails?
DevOps Agent automatically reverts the last commit, redeploys the previous known-good version, opens a GitHub issue documenting what went wrong, and sends a critical alert to your team. No manual intervention needed.
How do agents learn new capabilities?
SKILL.md — a dynamic capability discovery system. Drop a markdown file into the skills directory describing a new coding standard, runbook, or workflow. Agents discover it at runtime. No code changes, no redeployment.
Do you train on our code?
No. Every client gets isolated agent instances. Your code, logs, and data stay within your boundary and are never used to train shared models or visible to other clients.
Do you only build coding agents?
No. Code generation is one of 28 features. Our agents also handle incident diagnosis, testing, deployments, infrastructure provisioning, self-service data dashboards, cost reporting, architecture documentation, and more. We serve 7 personas: developers, tech leads, DevOps, SRE, QA, data analysts, and FinOps. Need a custom agent? Start with a free assessment.
What industries do you serve?
Any industry with engineering teams or operational workflows that benefit from AI automation. Banking, utilities, healthcare, fintech, SaaS — our agents work with any tech stack: AWS, GCP, Azure, GitHub, GitLab, Terraform, Jenkins, and more.
Ready to meet your autonomous engineering team?
Start with a free assessment. We'll scan your environment and show you what the agents can do in the first 10 minutes.