Software
that improves
Software.
We don't ask you to trust claims. We show our work.
- 01Import a repository.
- 02Prodia understands it.
- 03Finds opportunities.
- 04Validates changes.
- 05Improves it safely.
Six steps. One continuous loop.
Tap any step to see what's happening underneath.
Not a tool. A new category.
Three ways software gets better. Only one of them runs while you sleep.
Manual improvement
Humans read, decide, refactor, hope. Improvement is a meeting.
Session-based assistance
Helps in the moment. Forgets when the tab closes. No memory of what worked.
Continuous governed adaptation
Always learning. Always validating. Always reversible. Never asleep.
Connect Your Repository
Pick a source — public or private. Prodia clones, indexes, perceives, hypothesises, validates, and seals its first decision in under thirty seconds.
- Step 01● doneSourceGitHub · GitHub
- 02Step 02○ idleAuthorizeOAuth handshake pending
- Step 03◌ lockedConnectAuthorize the source to enable connection
- repo:readClone + index private repositories
- metadata:readResolve org / branch / commit refs
- checks:readCorrelate CI runs with hypotheses
- · envelope-encrypted (KMS)
- · per-tenant key isolation
- · rotated every 90 days
- · revoke any time
- · never logged or echoed
- · SOC 2 + ISO 27001
- activeGitHubactiveOAUTH · you@prodia.dev · scopes 3
- idleGitLabnot connected
- idleBitbucketnot connected
- idleAnsible Automation Platformnot connected
- expiringAzure DevOpsTOKEN · svc-prodia-indexer · scopes 2
- idleHarnessnot connected
- idleOctopus Deploynot connected
- idleAWS CloudFormationnot connected
- idleBitrisenot connected
Built for the Future of Software Development
Autonomous improvement requires governance, traceability, and trust. Prodia was designed from day one for all three.
Software Stops Improving
The Moment Engineers Stop Working
Traditional Development
- Improvements happen manually
- Technical debt accumulates
- Engineering capacity is limited
AI Coding Tools
- Generate code on demand
- No continuous operation
- No long-term learning
Prodia
- Continuous improvement
- Long-horizon operation
- Learns from outcomes
- Safely evolves software over time
Governed Adaptation, Continuously Validated
Prodia evaluates the codebase, identifies candidate improvements, validates them against baseline, and promotes only what survives measurement.
Measured software evolution
Adaptation is observed, measured, and recorded — not asserted.
Continuous validation
Every candidate change is tested against baseline before persistence.
Controlled adaptation
Changes operate within policy boundaries set by your organisation.
Rollback guarantees
Every change can be traced, validated, and reverted instantly.
Evidence-driven improvement
Outcomes inform the next decision — and the limits of the next claim.
Human-governed workflows
Authority, approval scope, and oversight remain with your team.
Beyond AI Coding
The next generation of software development is not better code generation. It is software that continuously improves itself.
The continuous improvement loop.
Eight stages, one signed cycle. Every revolution emits evidence, retires falsified work, and compounds the next decision. Click any stage to inspect what it consumes and what it emits.
Generate your first evidence bundle in 2 minutes.
Connect a public repo or pick a sample. We'll run a single shadow cycle and surface the highest-lift hypothesis.
Every claim should be measurable.
What follows is not a product tour. It is the experimental record of the system describing itself — methods, results, freshness, and a pointer into the decision ledger for each measurement.
Every promotion carries a reversible handle
No mutation enters production without a verified, exercised reverse path that restores signed state.
Rollback is exercised in shadow at promotion time. Promotion blocks if the reverse path fails to restore signed state and lineage parity.
- promotions tested
- 8,914
- ungoverned shipments
- 0
- rollback p95
- 1.4s
Open: rollback under partial-region failure is exercised in simulation only.
The Lineage Map
Every accepted mutation chains to its parent across epochs, and ports across repos through transfer hops. Compounding is not a metaphor — it is a graph you can trace.
Potential business value, framed as evidence — not promises.
Prodia is designed to help organisations explore measurable improvements in maintenance, velocity, consistency, and governance — each supported by ongoing evidence generation.
Lower maintenance overhead
Explore reductions in repetitive engineering work through governed automation.
Faster improvement cycles
Shorten the path from opportunity to validated change inside policy boundaries.
Operational consistency
Apply the same validation and rollback discipline to every change, everywhere.
Governance visibility
Surface what changed, why, under whose authority, and how it can be reverted.
Safer experimentation
Run controlled adaptation behind baseline protection and change isolation.
Compounding evidence
Build a measurable record of outcomes that informs the next decision.
We avoid guarantees. Every claim above is framed as a hypothesis tested against measured outcomes in your environment.
Five Agents. One Governed Pipeline.
Every Prodia decision moves through a transparent orchestration of specialised agents — observe the system thinking, in real time.
Engineer
Blueprint → Mutation
- Generate code mutations under blueprint constraints
- Apply diffs in isolated sandboxes
- Attach lineage & provenance metadata
- Diff strategy
- Sandbox topology
- Lineage anchor
- Signed diff bundle
- Lineage node
- Telemetry hooks
hover a node · click to lock the dossier
A swarm, not a script.
Twelve specialists, one cohesion.
The pipeline you saw earlier runs once per cycle. Underneath, a constellation of role-specific agents works the codebase in parallel — leasing regions, exchanging signed evidence, and escalating to a human the instant policy demands it.
- HANDOFFScout-01 → Refactor-02 · tangled call-graph in /billing/engine (depth 4)
- EVIDENCEAccessor-12 → Refactor-02 · focus ring restored across 7 components
- HANDOFFScribe-08 → Linguist-11 · 4 strings desynced from runtime intent
- LEASEMigrator-10 → DepCurator-06 · reserving db/migrations · TTL 12m · reversible
- ESCALATIONAuditor-05 → Human (sec) · scope drift in auth/session.ts — hold for co-sign
Intelligence you can watch accrue.
Hypotheses are discovered from production telemetry, validated in shadow, proven in canary, and graduated to policy — or falsified and retired. Every promotion is signed, every retirement is recorded. Nothing is silent.
Hypothesis mined from telemetry
Runs offline against production traffic
Live on ≤5% of scope, probes watching
Promoted into policy, falsifiable forever
Falsified or no lift, removed cleanly
Adopted hypotheses, compounding.
High falsification is a feature. It means the bar is honest.
Every promotion signed · every retirement recorded · nothing silent
Memory That Compounds
Every sealed epoch leaves Prodia smarter than the last. Scrub the timeline to watch heuristics crystallise, cross-domain transfers fire, and the failure index decay as memory compounds.
- Heuristics
- 13
- Transfers
- 9
- FI
- 71.1
- FI ↓
- 28.2%
- T-30analyticsinfraProbe-budget calibrationE215
- T-27platformpaymentsQuorum-gated rolloutE211
- T-24searchfrontendGraph-aware ranking signalE208
- T-21paymentsbillingIdempotency re-promotionE205
- T-18analyticsauthAnomaly-score gatingE201
- T-15frontendinfraIdle-budget schedulingE198
Built For Long-Horizon Autonomy
Most AI systems fail when complexity accumulates. Prodia was designed to sustain intelligent behavior across extended execution windows while preserving goals, governance, and operational safety.
One system. Five guarantees.
Governance is not a feature list. It is a single mesh — a policy kernel and five interlocked guarantees, each enforced on every change, every agent, every artifact.
Validation Gates
No change reaches main without clearing the gate stack: type · contract · perf budget · semantic equivalence · isolated execution.
Governance is a wired system, not a checklist.
Eight subsystems exchange signed signals continuously: policy verdicts, risk scores, lineage graphs, approval tokens, rollback proofs, rationales, ledger entries, and compliance attestations. Hover to trace any subsystem's dependencies; click to lock its dossier.
Audit Ledger
Hash-chained record
- Signed entries
- Replay bundles
- Every other subsystem
Six wired systems. One governed surface.
Rollback Integrity, Transfer Learning, Core Safety, Signature Protection, Risk Classification, and Validation Gates run as one live mesh. Trace any system to its peers, then take the controls for yourself in a free guided demo.
?gov=risk#governance-systemsRisk Classification
Continuous tiered scoring across every in-flight action. Tier crossings raise approver count; trip lines halt execution and arm rollback.
- Risk scores
- Trip signals
- Tier deltas
- Lineage scope
- Probe telemetry
- Historical falsifications
Walk the six systems in a free guided demo — no install, no card.
Step through Rollback, Transfer, Safety, Signature, Risk, and Gates on your own scenario. Prefer to read first? Open the trust dossier or book a 20-minute pilot briefing instead.
Five boundaries between intent and effect.
Every action travels a signed path: Human → Policies → Governance Layer → Agent Swarm → Actions. Each boundary is explainable, blockable, and auditable. Hover to inspect; click to lock a stage.
Governance Layer
Decision Court
- Plan validity & rollback proof
- Falsification tests passed
- Lineage & provenance complete
- Plans without rollback
- Unfalsifiable claims
- Stale lineage
- Signed verdict
- Hash-chained ledger entry
- Replay bundle
No stage can be skipped · every boundary is hash-chained to the next
Reclaim engineer-quarters, not headcount.
Every assumption is exposed. Tune toil share, automation lift, and debt yield to your own telemetry — the model recalculates in real time.
360 hrs / week sustained over 13w horizon
Projected lift in shipped increments / cadence, vs. unaided baseline.
Autonomous software engineering is a testable hypothesis.
We believe software can become more adaptive, more maintainable, and more resilient through governed, evidence-based automation.
We do not claim that autonomous software engineering is solved.
Our focus is generating evidence, measuring outcomes, and continuously improving safety, reliability, and effectiveness.
Claims require evidence
Every capability statement is bounded by what we have actually demonstrated.
Outcomes are published
We publish outcomes, limitations, and lessons learned as part of responsible development.
Status is honest
Demonstrated, validating, researching, future — each label means something specific.
Join The Founding Partner Program
Early Access
LimitedBe among the first teams to connect a repository and experience continuous autonomous improvement.
Request AccessDesign Partners
By invitationShape the platform alongside our research team. Deep collaboration on capabilities and roadmap.
Request AccessEnterprise Pilots
Approval requiredProduction-scale evaluation with full governance, audit, and compliance support.
Request AccessWhat If Your Software
Improved While You Slept?
Join the organisations exploring autonomous software evolution.