Forty-eight wired modules. Forty-three typed tools. One sealed evidence chain.
The agent runtime that runs the platform. It plans the work, asks before spending, executes typed Python tools, validates generation against real physics, self-heals when a quality gate trips, and seals the entire conversation into the same signed evidence bundle as Mock and Synthesize.
- Wired modules
- 48
- Planner tools
- 43
- Dispatch engines
- 17
- Evidence
- 9-artefact BLAKE3
| data_clean | drop_threshold=0.05 | ~5c |
| encode_categorical | method=onehot | ~3c |
| train_predictive | model=randomforest | ~12c |
| shap_explain | sample=200 | ~3c |
Forty-eight specialised modules. One coherent runtime.
Six families: planning & approval, cost & scheduling, physics validation, self-heal & resilience, code generation & review, evidence & narrative. Each module has one job. The 17 highlighted below are the core control surface; 31 more specialised modules are wired end-to-end in code (approval_timeout, contract_context, dataset_resolver, evidence_parser, executor_edsha, executor_eval, executor_steps_ml, grounded_output, hypothesis_tree, memory, moderation, observer, patch_planner, policy_adapter, prompt_registry, replan_evaluator, replay_bundle, retry_escalate, rseg_calibration, rseg_evaluator, scenario_selector, turn_context, validation_runner, budget, hagp_pause, mmd, retry_policy, surrogate, diff_builder, domain_prompt, dataset_context).
Planning & approval
4 modulesAgent Planner
Decomposes intent into typed step graph; estimates cost per node before any tool fires.
Plan Executor
Runs the graph with structured concurrency, retries, and per-step checkpointing.
Human Approval Gate
Pauses on high-cost or high-risk steps; surfaces a typed approval card to the operator.
Shadow
Dry-runs proposed plans against last week's data to surface regressions before commit.
Cost & scheduling
3 modulesCost Manager
Hard caps per project, soft caps per turn; halts when burn rate exceeds policy.
Cryptographic Audit Trail
Per-tenant compute throttle with full audit traceability; preempts low-priority work when high-priority arrives.
Engine-Level Scheduler
Routes work to the cheapest engine that satisfies the contract (Mock vs Synthesize vs ADS-driven).
Physics validation
1 modulesPhysics Validator
Constrains generation to physically-realisable signal shapes using a physics-honest response model.
Self-heal & resilience
5 modulesSelf-Healing Execution
Watches the evidence chain; if a quality gate fails, repairs the failing artefact and replays downstream.
Consistency-Aware Builder
Re-derives downstream artefacts when upstream inputs change so the evidence chain stays consistent.
Replan
Mid-run plan revision when an unexpected error or insight makes the original plan stale.
Risk Evidence Graph
Risk-stratified evidence graph; flags brittle or low-confidence sub-paths for review.
Cross-Correlation Rebuilder
Preserves PK/FK and joint distributions when artefacts are regenerated.
Code generation & review
2 modulesCode-Gen Critic
Reviews tool-generated Python before execution; rejects unsafe or undefined behaviour.
Code Change Manager
Versions every tool-generated Python; lets the operator diff and roll back at any step.
Evidence & narrative
2 modulesProof Packets
Bundles per-step inputs, outputs, hashes, and parameters into the signed evidence chain.
Narrative Generator
Produces a plain-English run-log alongside the JSON artefacts — for the audit reviewer.
Forty-three typed tools the agent can wield.
All five families are wired through both the chat interface and POST /v1/agent/tools/{name}/execute for direct invocation from the SDK or your own UI.
Data preparation
6 toolsMachine learning
7 toolsExplain & report
8 toolsSynthetic data
5 toolsIndustrial / ICS
6 toolsQuality gate fails? It heals itself.
When a K-S divergence widens, a constraint slips, or a hash mismatch appears, the self-healing layer isolates the failing sub-graph, repairs the affected artefact, and rebuilds the chain — without losing what already passed.
The narrative file gets a paragraph explaining what happened and why the rebuild is sound. Your auditor reads English, not commit hashes.
Sense
Self-healing execution watches every quality gate, every artefact hash, every chain segment in real time.
Diagnose
The risk-evidence graph isolates the failing sub-graph; the cross-correlation rebuilder identifies which downstream artefacts are now stale.
Repair
Replan rewrites the affected sub-plan; the code-gen critic reviews any generated code before re-execution.
Re-seal
The consistency-aware builder rebuilds the downstream chain; proof packets commit the new cryptographic root; the narrative generator appends to the run-log.
Every engine under one orchestrator.
The engine scheduler routes the work to the cheapest engine that satisfies the contract; the physics validator keeps generation physically realisable; proof packets seal the result.
Mock Data
Sub-minute deterministic synth from a prompt.
Synthesize
Our trained synthesis engine on uploaded data.
Virtual SCADA
Physics-honest sensor telemetry over real protocols.
ICS Security
Ground-truth ATT&CK ICS attack mix injection.
Tool executor
43 typed Python tools in-process or queued.
Connectors
14 encrypted source adapters, browse + import.
Built so an autonomous agent can survive procurement.
Tenant-isolated
Every plan, prompt, dataset preview, and tool I/O lives in your tenant prefix only.
Spend-bounded
Soft + hard cost caps; the agent stops, asks, or downgrades the engine before exceeding policy.
Audit-ready
Sealed transcript artefact per project — prompt, plan, approvals, tool I/O, evidence root.
Reproducible
Re-run the same sealed contract + seed on a different cluster: the dataset hash matches byte-for-byte.
Bring a real prompt. Watch every module work.
90-minute working session: bring a representative dataset and one open question. We drive the agent end-to-end, you watch the plan card, the cost gate, the live exec stream, and the self-heal trigger if a gate trips. You keep the sealed transcript bundle.