PRAE The control plane for enterprise agents.
Agents can reason, plan, and execute. They still can't carry the enterprise with them. PRAE grounds every action in organizational reality, verifies what execution proves, and compounds validated knowledge into context the next agent inherits.
Built your own agent? PRAE governs agents built into your applications — without a model or a proxy in the execution path. Custom agents →
- ◆ Sees each tool and API call your agent proposes
- ◆ Judges it at the execution boundary, before it runs
- ◆ Enforces deterministic policy: allow, refuse, hold
- ◆ Mounts in your own tool loop — keep your framework
AGENTS.md tells the agent. PRAE controls the agent. Keep the instruction files you already have — PRAE reads them, enforces the part that can be enforced, and seals what the agent was actually told.
Foundation Models · Agent Frameworks · PRAE — Control Plane · Enterprise Systems · Observability
The architectural problem
Enterprise agents can execute. They cannot reliably carry the enterprise with them.
The result: agents operate against an incomplete model of the enterprise — and knowledge never compounds.
Fragmented
Context is scattered
Enterprise knowledge lives across systems, schemas, repositories, policies, and people. Agents typically see only a partial slice of it.
Ephemeral
Execution disappears
When an agent solves a hard workflow or surfaces an edge case, the context behind that success rarely outlives the task.
Repeated
Nothing compounds
The next execution rebuilds the same retrieval, state, rules, and memory from scratch. Effort duplicates. Failures repeat.
Aha · Execution control
One execution, inside a fleet.
A simulated fleet of agents, running in your browser. Follow one execution to a crown-jewel resource, watch PRAE intercept it at the execution boundary, and steer what the agent does next. Every decision is the real PRAE kernel judging the call — not a model of it. Nothing is executed.
Runs entirely in your browser. No call leaves this page.
OWASP LLM TOP 10 2026 · EU AI ACT art. 12 · NIST AI 600-1 · SOC 2 CC7.2
The PRAE model
Ground · Verify · Compound
Every verified execution makes the next execution better grounded. This is the loop PRAE runs continuously beneath your agent workforce.
Ground & execute
ShippingDeterministically constrain what agents can do before they act.
- Structural / AST grounding
- Schemas & business rules
- Permissions & policies
- Pre-execution validation
Verify & compound
NextTurn execution into trusted organizational intelligence. Capture ships today; the three that follow it do not.
- Capture execution evidence
- Test & verify discoveries
- Promote validated patterns
- Re-inject context into future agents
Agentic workforce
Agents don't execute against a prompt. They execute against a continuously compounding, governed control plane.
The agentic control plane
Six capabilities. Four of them do something today.
Everything agents need to act with organizational fidelity — grounded, constrained, and continuously improving. Execution control is the one that runs end to end, and it is the one running in the page above. Three more do part of what they describe today, and two are still roadmap. Each is labelled for which.
We would rather you find the roadmap here than in the console.
Instruction ingest
In partToday: every AGENTS.md, CLAUDE.md and .cursorrules an agent would be given is read the way the harness reads them — operator files above project files, each statement carrying its file, line and layer — and the enforceable subset is proposed as rules you review, never applied. Anchoring those instructions to the code they talk about is the half still to build.
Context compilation
In partToday: a project context file is served to every agent in the profile and the whole assembled prompt is hashed into the decision ledger, so what the agent knew and what it did sit on one chain. Compiling that context — filtered by structural relevance, scope, trust, and task — is the half still to build.
Execution controls
ShippingExplicit constraints applied before execution — permissions, policies, paths, hosts, budgets. The operator baseline is intersected with what a plugin's author declared, and the operator can only ever narrow. Not to make agents less autonomous. To make autonomy trustworthy.
Run it in the playground →Evidence & verification
In partToday: every decision and every prompt assembly is written to a hash-chained log with the clause that produced it — a removed, edited or reordered row breaks the chain — and any row exports as a signed receipt a counterparty checks against a pinned key, without the ledger, our machine, or yours. Completeness is the half still to build: a signature proves a decision happened, not that no others did, and nothing yet binds a key to who holds it.
Read a chained ledger →Structural grounding
On the roadmapAnchor organizational knowledge to the systems agents actually operate within — repositories, services, modules, symbols, dependencies, call graphs, execution paths, and architectural boundaries. Context becomes structurally grounded, not disconnected text.
Enterprise ontology
On the roadmapVerified discoveries become structured, durable knowledge — architecture, workflows, constraints, failure patterns, and organizational rules. This is the compounding layer: every verified execution makes future ones better.
Products
Where PRAE governs execution.
Not only coding agents. The same execution control governs the agents on your developers’ machines, the agents your team builds, and the agents you deploy as services — each labelled for what ships today.
Agents, by environment
Developer agents → custom / homegrown agents → deployed SaaS agents
Governance
What applies to every agent PRAE governs
Where your agents operate: Cursor Claude Desktop Windsurf GitHub Copilot Slack AI (roadmap)Microsoft 365 Copilot (roadmap) every integration, at its real status.
AI compliance & audit readiness
Answer questions about AI risk and compliance with hard evidence.
Know what your agents were allowed to do. Know what they actually did. Prove it.
Policy → Decision → Execution → Evidence
- ISO/IEC 42001:2023 Mapped
- EU AI Act Mapped in part
- NIST AI RMF Mapped in part
- MITRE ATLAS Mapping planned
- OWASP Top 10 for LLM Applications 2026 Mapped
- Mapped controls and evidence support your programme; they are not a certification.
Evidence & verification
Knowledge earns trust. It isn't assumed.
DesignDiscoveries move through explicit trust states before they're allowed to influence future execution.
This ladder is the model we are building to, not a feature you can use yet. What exists today is the record underneath it — and the receipt below it, which is already yours to check.
Candidate
An unverified observation or hypothesis surfaced during execution. Noted, not trusted.
Corroborated
Supported by repeated or independent evidence across separate executions.
Verified
Backed by tests, reproducible behavior, static analysis, or deterministic verification. Eligible to enter the ontology.
Underneath it: a receipt anyone can check
ShippingEvery decision is hash-chained to the one before it, with the clause that produced it. Any single row then exports as a signed receipt — the decision, an Ed25519 signature over its seal, and the public key. Whoever holds it recomputes the row's hash and checks the signature against a fingerprint they already trust, needing neither the ledger, nor our machine, nor yours.
Bounded on purpose: a signature proves this decision happened, not that no others did — only the chain speaks to that, and only to you. The key stays in your custody, and nothing yet binds it to who holds it. Both are named on the roadmap above rather than papered over here.
Only verified knowledge becomes durable organizational intelligence.
The moat
A mall gets bigger. A garden gets richer.
Hyperscalers provide the infrastructure mall — compute, models, orchestration, storage. Essential, and the same for everyone. PRAE cultivates the enterprise-specific intelligence that makes agents effective inside your organization, specifically.
- Compute
- Models
- Orchestration
- Storage & networking
- Generic AI primitives
Gets bigger. Same for every organization that buys it.
- Architecture & dependencies
- Business rules & workflows
- Verified discoveries
- Failure patterns
- Domain ontology
Gets richer with every verified execution. Specific to your organization — and impossible to buy off the shelf.
Get started
Put a control plane above your agents — one that gets smarter with every execution.
For engineering leaders evaluating agentic infrastructure at enterprise scale.
One email to us, nothing stored. We reply from [email protected].
Agents execute.
PRAE makes sure they execute against what the organization actually knows, allows, and trusts.