AI has made individual developers faster, but most organizations still cannot turn that into consistent team delivery. Our Agentic SDLC Factory Platform is a complete, governed engineering platform: teams that work with agents, a shared brain, an agentic factory floor and cost control. It is built inside your environment and handed over to your teams.
The Platform is our full solution for scaling agentic engineering across your whole engineering organization, built on our Twelve Factor Agentic SDLC methodology. Building it creates four things inside your environment that work together. AI Transformation, the inner loop, moves your teams from individual AI use to one shared way of working with agents: we measure where you start, run hands-on workshops and embedded sprints on your own code, and hand over a working method with clear roles for developers and agents. The Agentic Factory Floor, the outer loop, takes every issue from intent to production through governed steps. Shared Brain holds your rules, skills and context in Git, so both loops draw on the same source. AI Cost Optimization acts as a control tower over both, keeping AI spend visible and within budget. Each is a Tikal solution you can start with on its own, and the Platform runs all four as one program.
The Platform runs on your existing stack: issue trackers, Git, IDEs, coding agents, LLM gateways, observability, containers, CI/CD and cloud. It is a model, coding agent and harness agnostic. The team-ai-directives repository holds the Shared Brain, and a central gateway manages routing, budgets and guardrails for all AI traffic.
Agentic engineering that scales across teams, with quality, control and cost under management.
Every developer works with agents in the same way, with shared workflows and clear ownership.
Rules, skills, context and evals live in Git and are reused by every team.
Specs, agents, verification, review and deployment run as one governed flow, with people at the key gates.
Budgets, model routing and context compression keep AI costs measurable and under control.
Automated checks, evaluator judges and human approval protect every change before it reaches production.
The factory, the repositories and the trained AI leads stay with your organization, with results measured against your baseline.
The Platform is implemented across your whole engineering organization one scoped batch at a time (up to 50 developers per batch). After an initial 10-day Discovery sprint to set your baseline and KPIs, the Platform is rolled out across four core stages. You can run each stage as a standalone solution (6 to 12 weeks) or combine them into an integrated Factory program before moving on to the next group.
Starting from the baseline of the Discovery sprint, hands-on workshops and embedded sprints on your real code then build one shared way of working with agents, and we create the first team-ai-directives repository.
We grow the first team-ai-directives repository into a full Shared Brain, with rules, skills, context modules and evals, versioned in Git and owned by your AI leads.
Our squad works inside your sprints to build intake, spec gates, separate test and code agents, sandboxes, evaluator judges and human approval points around your existing tools.
We place a central gateway in front of AI traffic for visibility, budgets, model routing and context compression.
At the end of the batch we measure results against the baseline agreed in the Discovery sprint and hand ownership to your internal AI leads, and agree with you whether to continue, adjust or scale to the next batch of teams.
Ready to scale?
Let's build your Agentic SDLC Factory Platform around the way your organization works.
