Skip to content
Sign inRequest Early Access

Companies don't have a data problem. They have an understanding problem.

Know what you've built.

OPSANA converts scattered engineering evidence into a living assessment of your software, risk and operational health. Rigorous for engineers, legible to everyone else.

Request Early Access
northwind/checkout-serviceread 12 Sep, 34,180 linesApproved
Confidence positionModerate
58.547.5–69.5
0, no evidence100, fully evidenced

Basis: 2 of 3 sources read. The range is wide because part of your system could not be reached, not because the findings are weak.

What could bite you

  • HighA refund can be issued twice if the first attempt times out.
  • HighNothing alerts anyone if the nightly reconcile fails.
  • MediumCurrency changes are not reflected in cached prices.

This is a real report shape. Read the whole sample, no sign-up. Open the sample report

Six questions most teams can't answer quickly.

  • Code
  • Jira
  • APIs
  • Tests
  • CI/CD
  • Cloud
  • Kubernetes
  • Logs
  • Metrics
  • Telemetry
  • Incidents
  1. 01What does this system actually do?
  2. 02Where is the hidden risk?
  3. 03What evidence do we have that critical behaviour works?
  4. 04What depends on this service?
  5. 05What happens when it fails?
  6. 06What don't we understand?

One intelligence layer across engineering and operations.

OPSANA connects the evidence already distributed across the engineering organisation and transforms it into structured, evidence-backed understanding, without replacing any existing tool.

  • Code
  • Git history
  • Jira
  • Documents
  • APIs
  • Tests
  • CI/CD
  • Cloud
  • Kubernetes
  • Logs
  • Metrics
  • Telemetry
  • Incidents

OPSANA

  1. Gecko reads builds the model
  2. A person approves what enters it
  3. Kraken derives tests from it

  • Context Graph

    What we understand.

  • Evidence Graph

    Why we believe it.

  • Risk Graph

    What could matter.

Read todayRoadmap

From engineering evidence to intelligence.

01 Observe

Build understanding.

Connect engineering signals into a structured model of what the system is and how it works.

Live

02 Predict

Identify hidden risk.

Surface technical, behavioural, dependency and operational risk before it becomes an incident.

Live

03 Simulate

Challenge assumptions.

Probe system behaviour and operational resilience through evidence-grounded simulation.

Roadmap

04 Assure

Validate important behaviour.

Generate and execute tests grounded in rules, invariants, risk and known system behaviour.

Generating is live. Executing is on the roadmap.

05 Navigate

Turn complexity into decisions.

Transform connected intelligence into clear, evidence-backed decision support for engineering leaders.

Live

06 Act

Automate with confidence.

Automate where evidence, governance and confidence justify it, never faster than trust allows.

Roadmap

Intelligence across the engineering lifecycle.

  1. 01

    Confidence

    Live

    How confident are we that this software will behave as expected?

    Build an evidence-backed understanding of complex software, identify hidden risk, generate grounded testing intelligence, validate behaviour and continuously learn from engineering and production evidence.

    • Understand
    • Validate
    • Execute
    • Simulate
    • Learn
    • Report

  2. 02

    Resilience

    Roadmap

    How resilient are we when things go wrong?

    Build a living understanding of infrastructure and dependencies, identify operational risk, assess reliability and recovery readiness, simulate failure and learn from incidents.

    • Infrastructure
    • Dependencies
    • Reliability
    • Simulation
    • Intelligence

  3. 03

    Product & Engineering Due Diligence

    By engagement

    What product and engineering system are we actually acquiring?

    Build an evidence-backed understanding of a software asset before an investment or acquisition, connecting product reality, engineering implementation, behavioural assurance, operational dependencies, risk and uncertainty.

    • Product Reality
    • Engineering Reality
    • Product Confidence
    • Operational Reality
    • Due Diligence Intelligence

Intelligence built on evidence.

Context Graph

What we understand.

A living model of capabilities, entities, business rules, journeys, services, dependencies, infrastructure and their relationships.

Context Graph: five entities from the sample repositoryCustomerOrderPaymentRefundLedger

Evidence Graph

Why we believe it.

Connects understanding and conclusions to code, APIs, Jira, tests, Git history, telemetry, deployments and incidents.

Evidence Graph: one claim linked to a file, a ticket and a testRefund at most onceservice.ts:214PAY-412refunds.spec.ts

Risk Graph

What could matter.

Continuously maps quality, technical, behavioural, dependency and operational risk across the evolving engineering system.

Risk Graph: four hotspots in the sample repository, longest bar is highest riskrefunds/jobs/reconcilepricing/cacheauth/session

Human Governance

AI proposes understanding and findings. Humans validate, enrich and govern important intelligence. The three graphs evolve together under human oversight.

Every answer should have evidence.

From a high-level finding, trace all the way to the engineering evidence that supports it. Select a trace node to explore.

Step 1 of 6

Refund Processing

High severity finding

A refund can be issued twice if the first attempt times out. Refunds are a payment capability, so a duplicate is money leaving the business.

Evidencerefunds/service.ts:214

Traced from the sample report, northwind/checkout-service.

Specialised intelligence. One connected system.

Each agent delivers specialised intelligence. All share the same evidence, context and risk foundation.

Confidence

  • Gecko Context Intelligence

    Live

    Builds evidence-backed understanding of software.

  • Kraken Test Intelligence

    Live

    Identifies and generates test intelligence grounded in rules, invariants, risks and state flows.

  • Cheetah Execution Intelligence

    Roadmap

    Executes governed tests and captures execution evidence.

  • Shark Production Intelligence

    Roadmap

    Learns from production behaviour, incidents and anomalies.

  • Swarm Simulation Intelligence

    Roadmap

    Challenges assumptions through behavioural simulation grounded in rules, invariants and state flows.

Resilience

  • Infrastructure Intelligence

    Roadmap

    Maps infrastructure and environments.

  • Dependency Intelligence

    Roadmap

    Maps system dependencies, critical paths and blast radius.

  • Reliability Intelligence

    Roadmap

    Assesses redundancy, backup, failover and recovery readiness.

  • Incident Intelligence

    Roadmap

    Builds incident understanding and supports investigation.

  • Chaos & Recovery Simulation

    Roadmap

    Simulates infrastructure failure and recovery scenarios to surface operational risk and blast radius.

Shared

  • Eagle Reporting & Decision Intelligence

    Roadmap

    Transforms intelligence into clear reporting and decision support for engineering leaders and stakeholders.

AI-assisted. Human-governed.

OPSANA uses AI to discover, infer, analyse, simulate and report. Humans remain responsible for validating important context, governing authoritative knowledge and determining when automation is appropriate.

This is not an AI that replaces engineering judgement. It is an intelligence system that makes engineering judgement better.
  1. 01AI discovers and infers
  2. 02Evidence supports every conclusion
  3. Human validates and governs
  4. 04Governed intelligence emerges
  5. 05Decision or governed action

Your systems change.

Your understanding should too.

Software changes. Infrastructure changes. Incidents reveal new evidence. Tests reveal new behaviour. OPSANA's intelligence models evolve with the engineering system.

A scanner
Produces a report.
OPSANA
Builds a living intelligence model of your engineering system.

The same repository, read four times

Confidence position, 0 to 100, with its interval

05010031 to 79Read 1Code onlyRead 1, 15 Aug: 31 to 79, width 48. Code only.41 to 74Read 2Jira connectedRead 2, 29 Aug: 41 to 74, width 33. Jira connected.47.5 to 69.5Read 34 questions answeredRead 3, 12 Sep: 47.5 to 69.5, width 22. 4 questions answered.53 to 67Read 43 more answeredRead 4, 26 Sep: 53 to 67, width 14. 3 more answered.

Each answered question and each new source narrows the range. The model keeps what it learned.

Twenty-five seconds, if you would rather watch.

It reads everything, fast. Then it reaches the one thing your code cannot tell it, and it stops and asks a person.

Your engineering systems already contain the evidence.

OPSANA turns it into understanding.

Request Early AccessTalk to us