How we deliver Azimuth
We install Azimuth on your codebases, then hand you the keys.
Azimuth is not a tool you download and hope for the best. It is an engagement: you prove the framework on your own work before any big commitment, and we build the capability so your team runs it without us. Here is how that works.
Delivery discipline
How we work, day to day
The same delivery discipline runs on every engagement. It is what keeps AI-assisted work safe to ship in an enterprise.
Discuss before we build
We propose the approach, list what it touches, and wait for your go-ahead before changing anything.
Test first
A failing test, then the minimal implementation, then the refactor. The discipline that keeps AI output honest.
Verify against the requirement
We check the work against acceptance criteria and real evidence before anyone calls it done.
Quality gate before merge
Correctness, tests, security, and architecture reviewed in a single pass, before code lands.
Security on every endpoint
Every new endpoint, form handler, or auth change gets a security review. Not optional.
A record for every decision
A root-cause document per ticket and a full audit trail of what the AI did and why.
SDLC 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
Capability transfer
Built to be handed over
The point of the engagement is for your team to run Azimuth without us. We skill your experts first. They become the owners and trainers, not dependents on a vendor. The work happens on your real codebase while a coach narrates the skill being used. Intake and exit scorecards make the change visible.
That training is grounded in a curriculum of ten concrete skills for working with AI agents, each scored, each coachable. It runs alongside the consulting, not in a classroom.
See the ten-skill curriculumOn your infrastructure
Azimuth runs on your infrastructure. Your code, requirements, and decisions never leave your network. As long as you are an active Azimuth customer, everything we build with you is yours to use: the knowledge graph, the agent customizations, and the integrations.
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.
Deliverables
What you receive
Concrete output from the first engagement, measured on your own data and running on your own infrastructure.
- A day-one baseline measurement of your delivery today
- Your codebases indexed and queryable by every agent
- Your existing tools connected: Jira, Confluence, CI, observability
- An agent roster tuned to your stack and conventions
- Your team trained on the workflow and the governance protocol
- A full audit trail of every AI action
- While you are an active customer: the knowledge graph, customizations, and integrations are yours to use
The engagement
The engagement, phase by phase
We do not ask you to take the framework on faith. Each phase delivers value on its own, and you decide when to take the next step.
Discovery
A paid advisory engagement. We audit your codebases, map your toolchain, and chart where AI capability lands first: which teams, which work, which quirks of your systems the framework needs to learn. 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: a real evaluation on your own codebase, not a sandbox demo. At day 30 you make one decision: commit, or walk away.
Capability Transformation
A fixed-scope implementation. We install the framework on your infrastructure, tailor it to your codebase's quirks, connect your existing systems, and skill your experts first, so they become the owners and trainers, not dependents on a vendor.
Capability Licence
A flat per-team annual subscription that delivers quarterly framework updates. Models change fast; the licence keeps the framework adapting with them. Ongoing advisory runs on a time-and-materials basis. It still runs on your infrastructure. This is not a multi-tenant service.
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.
Next step
See whether it fits your team
Book a discovery call. We will map your current delivery process with you and show you where Azimuth creates leverage. No commitment, just an honest conversation.