One model.
Fourteen jobs.
Your tools each hold a partial picture of the same system. Sembix Strata™ runs the whole lifecycle against one model derived from your codebase — from a COBOL mainframe to a TypeScript service.
The problem is the seams, not the count
Most engineering organizations run between six and ten separate tools to build software — 7.4 on average, in a 2025 survey of 300 IT professionals at organizations with 150+ developers. Each holds a different partial picture of the same system, and none of them can see the others. You could consolidate a dozen tools into one and gain nothing, if the one tool still kept a dozen separate pictures of your system.
What makes a toolchain expensive isn't the number of invoices. It's that your architecture diagram doesn't know what your dependency scanner found. Your tracker doesn't know which service a ticket touches. Your roadmap can't tell you two initiatives hit the same module. Your coding assistant has never read your standards. Integrations move records between tools — they don't give the tools a shared understanding.
Strata derives one model from your repository — entities and the typed relationships between them, modules, business domains, user journeys, data models — and every capability reads from it. The seams aren't integrated. They aren't there.
The difference that matters
Derived, not drawn
A diagram you draw is out of date the moment you commit. A model derived from your code is only ever as stale as your last analysis run.
A drawing surface
Someone has to keep it true, and nobody does. The diagram, the service catalog and the inventory spreadsheet all decay the moment attention moves elsewhere — and the team quietly stops trusting them.
A derived model
Strata reads your version-control history and builds the picture, then rebuilds it as the system changes. Entity graphs, module dependencies, the external boundary, user journeys, per-domain data models. Journey and data-model diagrams export to PDF or SVG; the architecture views package into a PDF report.
Because the model is built by reading meaning rather than parsing syntax, it isn't restricted to languages someone has written a parser for. A COBOL system on a mainframe produces a semantic model the same way a TypeScript service does.
Thirteen categories, one model
Each of these is an established market with its own vendors, its own renewal date and its own partial view of your system. Strata does the job against the model instead.
Architecture diagramming & modeling
Someone draws the system; it's stale by the next sprint.
Diagrams derived from the code and regenerated every analysis run — entity, module, service, dependency-boundary, journey and data-model views.
Internal developer portal & software catalog
A catalog of services, owners and dependencies, hand-registered and hand-maintained.
The catalog is the derived model. Entities and the typed relationships between them come from the repository, not a registration form.
Code comprehension & code search
Helping engineers understand an unfamiliar codebase.
Five layers, from commit-level facts up to business domains and user journeys. Meaning, not just symbols — in any language, including the ones no parser supports.
Application inventory
An inventory of applications and capabilities for rationalization.
Capability and entity inventory exported straight from the model.
Static analysis & code quality
Finding issues in code against generic rules.
Your own codified standards, evaluated with confidence scores and file-and-line evidence — not a vendor's idea of good practice.
Compliance automation
Evidence collection against a control framework.
Compliance packs that reach the coding agent, are reviewed again before the change ships, and track drift afterwards. One loop, not a separate evidence system.
AI code review
A bot comments on pull requests.
A standards review before the change ships, with per-standard verdicts, evidence and severity. Shipping past open findings asks for a written reason, kept in an append-only audit log.
AI coding assistants & agents
Writing code faster.
Seismic Mode: a bounded agent loop with explicit, measurable verification criteria, holdout checks the agent can't read, and budget ceilings on iterations, steps, tokens, time and spend. A run pauses at the first ceiling it reaches and asks before spending more.
Project & issue tracking
Where the work lives.
A built-in tracker and board — or push epics and features into the tracker you already run, with traceability back to the source.
Roadmapping & portfolio management
Deciding what gets built when.
Roadmap scenarios computed against the backlog and the links between issues. The planning agent stages changes to the plan; a human applies them.
Software engineering intelligence
Cycle time, throughput, burndown.
The same metrics from the same model — with an agent-versus-human split that a bolt-on analytics tool cannot produce. Stations shows every workspace at work right now: live spend, run state and what landed.
Legacy & mainframe assessment
Specialist tools, or a consulting engagement, to work out what a legacy system does.
The same semantic model, built from COBOL and mainframe sources as readily as from modern ones. Strata reads meaning rather than parsing syntax, so it isn't limited to languages someone wrote a parser for.
Preview & development environments
Somewhere to run the branch.
Ephemeral preview environments booted from your own devcontainer.json, so an agent can drive a real browser through a journey while you watch.
And one with no vendor at all
There is no established market for software delivery estimation. There are parametric tools with defense heritage, forecasting add-ons inside analytics platforms, and spreadsheets. Mostly spreadsheets.
Strata sizes the backlog it generated — six evidence-backed dimensions per item, mapped to a T-shirt size — and projects delivery cost and duration from it. Estimated from the actual work, not from a planning-poker session someone has to run.
Why this matters more now
DORA's 2025 research found that AI raises throughput and degrades delivery stability at the same time — and that a high-quality internal platform is the foundation that unlocks AI's value.
That is the problem Strata was built around, and Seismic Mode is the answer to it. Agents don't run loose. Every run starts from criteria that can actually be measured — a command, a test, a standards check, a judgement, a human sign-off — and a criterion this deployment can't evaluate is refused before the run starts, rather than silently skipped. Some criteria are held back from the agent entirely and run only by the evaluator, because an agent that can read the test it's graded on will satisfy the test instead of the requirement.
It runs against five budgets — iterations, steps, tokens, wall clock and spend — and pauses at the first one it reaches and asks before spending more. If it stops converging it parks and asks for a hint, because not converging is a question rather than a verdict. Work lands on its own branch as a reviewable diff and an unmerged pull request. The loop can decide it is finished; it cannot decide the change ships.
Seismic Mode is available to selected customers — ask us about it when you book a demo.
Governance that closes the loop
Your standards reach the agent while it works, are reviewed again before the change ships — shipping past open findings takes a written reason, kept in an append-only audit log — and are tracked as drift after.
One trail, not four systems
Compliance packs cover ISO 27001, ISO 42001, WCAG 2.1 AA and application-security baselines. The ISO packs are scoped to the controls that can be evaluated from source code — the honest subset, and the one you can actually automate.
Fewer vendors to authorize
FedRAMP has authorized just over 500 cloud services since 2012, and legacy authorizations still run 12–24 months. At state level there is no single standard. Every additional vendor is another authorization package, another monitoring stream, another renewal — in every jurisdiction you operate.
The fair objections
“A specialist tool is deeper than a platform module.”
Often true, and we won't pretend otherwise. If you need the deepest static analysis engine on the market, buy it. What a specialist can't give you is the join — its findings don't reach your coding agent, your roadmap or your audit trail without someone building that bridge and maintaining it. We compete on the connections, not on feature parity in any single box.
“We'd be locked in.”
Journey and data-model diagrams export directly, architecture views package into a report, and the inventory exports as CSV. The backlog pushes into the Jira or GitHub you already run, as real epics and features with traceability links back to the source. Previews boot from your own devcontainer.json. Reports package up for people who don't have a Strata account. If you leave, you leave with your work.
“We're not replacing our stack.”
Nobody is asking you to. Strata pushes into the tracker you already use and reads repositories where they are. Teams typically start with one system and one question — what is actually in here — and let the rest follow.