AI Governance for your organization
Many sources of context. One governed line of action.
Azimuth grounds AI agents in your full project context, under governance you control.
What it changes
Context engine
A compact structural view of your codebase keeps prompts short and developers in flight on multiple items at once.
Governance reporting
Quality trends and a full audit trail drawn from real project data. Deterministic, no manual entry.
Institutional memory
Past decisions, abandoned approaches, and constraints persist across sessions and teams.
Where to start
30-day evaluation
We work with one of your teams to get the most value out of the framework, on your own work. Commit or walk away at day 30.
Start the evaluationFree diagnostic
Score your delivery readiness in ten minutes and see the three gaps to address first. No sales call.
Run the diagnosticTalk to a practitioner
A working session with the people who built the framework, not a pitch deck.
Book a callThe operating model
The Four Pillars of Azimuth
1. Context
What does the AI need to know?
Azimuth synchronizes your requirements, tickets, code, tests, environments, production logs, and decisions into a coherent, AI-queryable system. Every agent works from full project context, not guesswork.
2. Knowledge
What can the AI do?
Purpose-built capability agents handle planning, implementation, bug fixing, code review, security analysis, testing, deployments, log analysis, and more. Each is specialized, project-aware, and aware of your conventions.
3. Verify
Is it correct?
Requirements-driven testing. Acceptance criteria verification. Production evidence. A feature is not done until it is proven, not just "tests pass."
4. Govern
Should the AI do this?
Roadmap-first creation. Ownership boundaries. Human approval at meaningful risk points. Full audit trail. AI that does what it should, and only what it should.
The context gap
Six gaps code generators leave open
Code generators are good at what they do. But they run without your organizational context. Closing that gap is what the Context pillar is for.
| Gap | What it costs you |
|---|---|
| They don't know your requirements | AI writes code that passes tests but misses the spec |
| They don't know your ticket history | Same investigation repeated across sprints, wasting days |
| They don't know past decisions | AI proposes approaches your team already tried and rejected |
| They don't know your environments | Deployments that "work on my machine" but break in UAT |
| They don't enforce governance | Uncontrolled AI generation with no quality gates, no audit trail |
| They can't reason across repos | Changes in Service A silently break Service B |
Azimuth fills every one of these gaps.
Capabilities
What Azimuth can do for your team
Azimuth ships with governed capability agents spanning every phase of your SDLC. Each is customized to your stack, conventions, and toolchain during onboarding.
Planning & Requirements
- Requirements query and gap analysis against your documented specifications
- Efficient ticket queries: counts, summaries, full detail on demand
- User story generation with acceptance criteria
- Sprint breakdown and dependency mapping
- Cross-requirement traceability to code
Design & Architecture
- Architecture decision record (ADR) authoring
- Structural impact analysis before changes
- Cross-repo dependency discovery and documentation
- STRIDE threat modelling before implementation
- Pattern proposals with rationale and trade-offs
Implementation
- Feature implementation across all layers (data → service → UI)
- Test-driven development with Red-Green-Refactor enforcement
- Bug investigation, root cause analysis, and fix, end to end
- Refactoring with behaviour preservation and test validation
- Code generation tuned to your stack, conventions, and patterns
Quality & Testing
- Automated code review against project conventions and OWASP
- Acceptance criteria verification against requirements
- End-to-end test authoring and execution
- Supply chain security assessment (SBOM, SLSA)
- Quality gate enforcement before merge
Security
- OWASP Top 10 scan on every endpoint and form handler
- Secrets detection in commits and config
- Injection, XSS, and authentication vulnerability analysis
- Security review delegated automatically on auth changes
- Adversarial challenge mode: AI argues against its own proposals
Operations & Observability
- Production log analysis across your observability stack
- Root cause analysis document generation from live logs
- Incident timeline reconstruction from metrics and traces
- Runbook authoring from operational patterns
- AIOps: predictive detection from your production metrics
Positioning
How Azimuth compares
Your team already runs tools like these. Azimuth doesn't replace them. It's the operating-model layer that makes every tool more effective.
| Tool / Approach | Their strength | Azimuth's differentiator |
|---|---|---|
| GitHub Copilot Enterprise | Distribution, Microsoft brand, deep IDE integration | Copilot generates code from prompts. Azimuth is the delivery operating model that gives Copilot full project context, making it more effective, not replacing it. |
| Microsoft HVE Core | A large agent library with real toolchain plugins, installable under a permissive licence | Tool integration is not traceability. HVE connects to your tools. Azimuth carries the requirement through to the commit and the test that proves it, keeps the decision history in reach, and holds the approval gates. HVE agents run inside Azimuth as task workers. |
| Open-source agent frameworks | Fast-moving, permissive licences, strong day-to-day developer ergonomics | Approval settings a session can switch off are not governance. Azimuth enforces a safety floor no setting can lower: destructive operations always stop for a human. Multiple repositories are a governed registry, not a folder list in your editor. |
| Cursor / Windsurf | A polished code-editing experience | IDE-locked tools. Azimuth is a process layer, not an editor. It adds the organizational context an IDE can't carry. Built for Claude Code. Supports GitHub Copilot. Extendable to other AI tools as required. |
| Devin / SWE-Agent | High autonomy: runs end-to-end without developer input | Autonomy without a floor is a procurement problem. Azimuth runs governed: human approval at meaningful risk points, a safety floor no setting can lower, and an audit trail that ties every action back to the requirement behind it. |
| Big 4 / IBM Consulting | Trust, scale, global delivery capacity | No product. Every engagement is bespoke and slower. Azimuth gives our consulting a head start on methodology and produces reproducible outcomes across every client. |
| Atlassian Intelligence | Already embedded in the tools your teams use | Platform features stay inside the platform. Azimuth is the operating model above your whole toolchain, using Atlassian as one context source alongside code, tests, and production evidence. |
| Atlassian Rovo | AI search and agents natively integrated with Confluence and Jira | Azimuth uses Atlassian as a context source and adds what a content index does not carry: requirements traced through to the code and tests that satisfy them, and an RCA drafted on the incident itself. It works the same way across non-Atlassian toolchains. |
Azimuth is a structured, opinionated AI delivery operating model. It plugs into the toolchain you already run, keeps your team's past decisions in reach, and enforces governance. The consulting makes sure it actually gets used.
What we deliver
Every rollout is a hands-on engagement
Azimuth is not a download. You prove it on your own work before you commit, and your team ends up able to run it. Four steps, each delivering value on its own.
Discovery
A paid advisory engagement. We audit your codebases, map your toolchain, and chart where AI capability lands first. You leave with a plan you can act on, with or without us.
30-Day Evaluator Licence
We work with one of your teams and ensure they get the most value out of the framework: thirty days on your own work, bounded by the scope you choose, before any commitment.
Capability Transformation
A fixed-scope implementation. We install the framework on your infrastructure, tailor it to your codebase's quirks, and skill your experts first, so they own it and teach it.
Capability Licence
A flat per-team annual subscription covering quarterly framework updates, so the framework keeps adapting as models change. Ongoing advisory runs on a time-and-materials basis.
On commitment
The Capability Licence
When you commit, the Capability Licence keeps the practice current. It is a flat per-team annual subscription that delivers quarterly framework updates, so the framework keeps adapting as models change and your experts stay the owners. Ongoing advisory runs on a time-and-materials basis. The framework still runs on your infrastructure; this is not a multi-tenant SaaS.
Ask about the Capability LicenceQuarterly Updates & Health Checks
Each quarter you get the latest framework release plus a structured review of agent accuracy and quality-gate pass rates.
Agent Tuning & Optimization
Ongoing refinement of agent definitions, skill modules, and context configuration as your team conventions and codebase evolve.
Custom Skill Development
New skills authored for proprietary frameworks, new toolchain integrations, or domain-specific workflows discovered post-rollout.
Escalation Support
Named support contact for complex agent failures, codebase onboarding, or governance questions, with agreed response SLAs.
Quarterly updates and health checks ship with the licence. Agent tuning, custom skill development, and escalation support are scoped as time-and-materials advisory.
Measured, not promised
Governance reporting, drawn from your own data
Every Azimuth deployment includes governance reporting drawn from your real project data: agent quality trends and a full audit trail of what the AI did and why. Reports run deterministically, with no manual entry and no model dependency.
Your tech lead sees the quality trends; your compliance team gets the audit trail. It comes from your environment, not a number printed on a marketing page.
AI skills curriculum
The framework, the process, and the skills to use them well
Teams get AI trust wrong in two directions. Over-trust ships the AI’s mistakes. Under-trust abandons AI after one error. Both are the same missing skill, and most “AI training” doesn’t teach it: it’s either prompt tricks that age out in a quarter, or generic AI literacy you can’t measure. Our curriculum is neither. It names the ten things you actually do, or fail to do, when working with an AI agent, scores each one on a five-point scale, and makes improvement visible.
It runs alongside the consulting engagement, not in a classroom. The coach narrates the skill being used while real work happens. Intake and exit scorecards make change visible. A follow-up assessment later in the year checks that the habits stuck.
Calibrating AI confidence
The AI sounds equally sure when it’s right and when it’s wrong. Treat confident answers as guesses until you’ve checked them.
Knowing when to push back
Spot the moment the AI is agreeing too eagerly, inventing an API, or quietly dropping a constraint. Then redirect it instead of absorbing the bad output.
Naming the missing context
The AI doesn’t know your codebase quirks, last week’s decisions, or your customer’s environment. Tell it, instead of waiting for it to ask.
Discuss versus directive
Know when to think out loud with the AI and when to authorise it to act. Both extremes fail: endless dialogue, or executing too early.
Structured problem decomposition
Break a vague ask into a sequence of small, specific questions the AI can actually answer well.
Iteration cadence
Know when to refine the current attempt and when to scrap it and re-prompt from a different angle. Refining for too long is the most common failure.
Tool, context, and model choice
Pick the right model, the right context to attach, and the right rules for the task. Top-tier for everything wastes money. Mid-tier for everything wastes the leverage.
Recognising sunk cost
Throw out two hundred lines the AI just wrote the moment you realise the premise was wrong. Don’t defend the work because the AI already did it.
Verification discipline
Treat every AI answer as a guess until something independent confirms it: a compile, a test, the actual docs, a second source.
Emotional regulation
Stay steady when the AI mis-fires and stay critical when it nails one. The last interaction shouldn’t decide the next.
How each skill is scored: 1 to 5
Ten skills, five points each, fifty in total. A low score points to the full curriculum. A middling score points to focused coaching on the lowest three skills. A high score shifts the engagement toward capturing what your team already does well, so the rest of the practice can learn it.
Free ten-skill diagnostic
Score your team against the ten skills in about ten minutes. You get a per-skill rating, a band placement, and the three skills to address first. No sales call required.
Who it’s for
Built for your organization
A whole software practice with established codebases, formal SDLC processes, and existing tooling: engineering, product, BA, QA, release, and design. AI that works withevery role’s process, not around it.
- Established codebases that have been around for years
- Mixed technology stacks across multiple repos
- Existing tooling (Jira, Confluence, Jenkins/ADO)
- Pain from slow onboarding and undocumented decisions
- AI adoption without governance or audit trail
Only the largest enterprises can afford to build a fully custom AI platform from scratch. Everyone else is left with a self-service tool that generates code without the context of your requirements, your decisions, or your systems.
Azimuth is built for you: a governed, ready-to-adopt option that gives AI your full project context, without a full in-house build.
Runs entirely on your infrastructure
Azimuth installs into the environment you already run. Your code, requirements, and decisions stay inside your network.
Your code never leaves your infrastructure. Azimuth runs on-premise. No source code, requirements, or internal data is transmitted to or stored by us.
Only the AI tools you authorize. Source, requirements, and decisions are sent only to the AI providers you approve. Never anywhere else.
Governed by design. Human approval at meaningful risk points, quality gates before merge, and a full audit trail of what the AI did and why.
Where is Azimuth heading?
From developer augmentation today, to bounded delegation tomorrow, to full lifecycle orchestration as AI matures. See how the framework grows with you over time.
Questions
Frequently asked questions
How is this different from GitHub Copilot Enterprise?
Copilot generates code from prompts. Azimuth is the delivery operating model that gives AI full project context, enforces governance, and preserves institutional memory. The two are complements. Azimuth makes the AI tools it supports more effective.
Which AI tools does Azimuth support?
Azimuth is built for Claude Code. It supports GitHub Copilot. It is extendable to other AI tools as required.
Do we need to change our existing tools?
No. Azimuth connects to your current toolchain and uses what you already have: Jira, Confluence, Jenkins, Azure DevOps, GitHub, Bitbucket, Grafana.
How long until we see results?
The pilot delivers value on real work on your actual codebase: bug fixes, code reviews, test generation, documentation. Engagement length is scoped per customer.
Does our code leave our infrastructure?
No. Azimuth runs on your infrastructure. Your code, requirements, and data never leave your environment. Regulated buyers can run it with zero outbound connectivity.
Can we customize the agents?
Yes. Every agent is customizable to your conventions, naming patterns, technology stack, and workflow. The consulting engagement tunes them to your team. Custom skills are a first-class part of the framework. Your teams can author, version, and distribute their own under framework governance.
What governance reporting do we get?
Azimuth includes governance reporting that draws on your real project data: agent quality trends and a full audit trail. Reports run deterministically, with no manual data entry. Your tech lead gets quality trends; your compliance team gets the audit trail.
What is your SOC 2 posture?
A SOC 2 readiness program is in place covering Security, Availability, Confidentiality, and Processing Integrity. Your code, activity log, and tokens are deliberately outside our audit boundary because they stay on your infrastructure.
Ready to make your AI understand your business?
Book a discovery call. We'll map your current delivery process and show you where Azimuth creates leverage. No commitment, no pitch deck, just an honest conversation about whether this fits.