The intelligence layer for complex engineering systems.
OPSANA sits above the existing engineering toolchain. It does not replace your tools. It builds a living, evidence-backed intelligence model of what your systems are, how they behave and where the risk lies.
Eight principles. One coherent intelligence model.
Signals and artefacts are connected.
OPSANA ingests code, Git history, Jira, tests, CI/CD runs, cloud configuration, Kubernetes state, logs, metrics, telemetry and incident data, and connects them into a unified evidence space.
Today: code, Git history, Jira and documents.
Structured understanding is created.
A Context Graph is built: a living model of capabilities, business rules, entities, journeys, services, dependencies, infrastructure and their relationships. What the system is and how it works.
Understanding is linked to evidence.
Every element of the Context Graph links back to the specific artefacts that support it via the Evidence Graph. Every understanding has a source. Every conclusion has a reason.
Risk and uncertainty are identified.
The Risk Graph continuously maps quality, technical, behavioural, dependency and operational risk. Uncertainty, where evidence is incomplete, is surfaced as a first-class signal.
Important context is governed by humans.
AI discovers and proposes. Humans validate, enrich and govern. Governed understanding enters the authoritative knowledge layer. Ungoverned understanding remains candidate intelligence pending review.
Tests, simulations and decision evidence are generated.
Grounded in the Context, Evidence and Risk graphs, OPSANA generates testing intelligence, simulation scenarios and decision support, all traceable to the understanding they came from.
Test generation is live. Simulation is on the roadmap.
Outcomes provide new evidence.
Test results, simulation outcomes, production incidents and deployment events feed back into the evidence layer. What the system does in practice updates what OPSANA understands about it in theory.
Roadmap.
The intelligence models evolve.
As the engineering system changes, the Context, Evidence and Risk graphs update. OPSANA is not a one-time scan. It is a continuously evolving intelligence model of your engineering system.
Three graphs. One connected intelligence model.
Context Graph
What we understand.
A living model of capabilities, entities, business rules, journeys, services, dependencies, infrastructure and how they relate. The Context Graph is the foundation everything else is built on.
- Capabilities and business rules
- Services and dependencies
- Infrastructure and environments
- Relationships and state flows
Evidence Graph
Why we believe it.
Connects every understanding and every conclusion to the engineering artefacts that support it. Code, tests, Git history, Jira, telemetry, deployments and incidents all contribute evidence.
- Code and API artefacts
- Test results and coverage
- Git history and Jira tickets
- Telemetry, incidents and deployments
Risk Graph
What could matter.
Continuously maps risk and uncertainty across the engineering system. Identifies what is fragile, what is unknown and what requires attention, before it becomes a problem.
- Technical and quality risk
- Behavioural and dependency risk
- Operational risk
- Uncertainty and evidence gaps
Human Governance Layer
The three graphs operate under human governance. AI discovers and proposes. Humans validate, enrich and govern. This is what makes OPSANA intelligence trustworthy enough to act on.
Multiple services. One intelligence foundation.
Confidence, Resilience and Due Diligence are not separate products. They are different applications of the same intelligence platform, sharing the same graphs, the same evidence and the same governance model.
Your engineering systems already contain the evidence.
OPSANA turns it into understanding.