AlphaBitCore
Platform

The AI Control Plane for regulated enterprises.

One governed runtime for models, agents, tools, skills, and workflows — built for firms with real compliance, audit, and risk exposure. This page explains what it is, how it fits, and what you get.

Under, beside, or instead of your stack?

A full agent platform. Every upper layer swappable.

AlphaBitCore ships Planner, Orchestrator, Agent Runtime, and a Skills & Tool Registry. Use ours, bring your own LangGraph, Bedrock, Temporal, or MCP, or mix. The Gateway and Event Stream are the non-negotiable control plane every effectful action passes through.

How AlphaBitCore plugs into your AI stackThree-column architecture diagram. Left: four swappable agent-stack layers — Planner, Orchestrator, Agent Runtime, Skills and Tool Registry — each showing ABC’s component or your bring-your-own alternative (LangGraph, Bedrock, Temporal, Step Functions, MCP servers, custom). Middle: AlphaBitCore Control Plane with Govern, Gateway as the single enforcement point, Effect (Agent Runtime), Sealed Event Stream, and benchmark stats. Right: audit-ready output — EAC, replayable execution, supervisory audit report, regulatory mappings, cost and usage attribution. Animated amber pulse traces an effectful action from the agent stack through the control plane out to attestation.How AlphaBitCore plugs into your AI stackUpper layers are swappable — use ABC’s, bring your own, or mix. The Gateway and Sealed Event Stream are not.Your Agent Stackuse ABC’s, bring your own, or mixAlphaBitCore Control Planealways ABC · runs in your VPC or on-premAudit-Ready Outputprovable by designPlannerABC Planner— or LangGraph · CrewAI · AutoGenSwappable layerOrchestratorABC Orchestrator— or Temporal · Step FunctionsSwappable layerAgent RuntimeABC Runtime— or LangGraph runtime · customSwappable layerSkills & Tool RegistryABC Registry— or MCP servers · internal APIsSwappable layerEvery effectful actiontool calls · DB writes · trades · filings · external APIsproposed via SDK / HTTPGovernone policy · scope, authority, capability bindingsGatewayone enforcement point · signed allow / denyno side channels · non-bypassabledenied actions produce zero state changeEffect — invokes models / APIs / systems of recorddurable mutation only within authorized scopeSealed Event Stream (ECES)tamper-evident · append-only · replayable≈ 1.1 KB per 8-event execution~2.7 msOverhead / exec4.4%At 50-way batch10,000 / 10,000Attack traces rejectedEACexecution attestationsigned, per-executionReplayable executionre-run from sealed streamSupervisory audit reportcausal chain, not screenshotsRegulatory mappingsFINRA · SR 11-7 · NIST AI RMFCost & usage attributionper workflow, at the GatewayComposes with what you already run — without changing your agent code. The Gateway and Sealed Event Stream are the non-negotiable control plane every effectful action passes through.Swappable — your code or ABC’sAlways ABCyour agent actionaudit / compliance pulled out
Definition

Effectful action.

An AI action is effectful when it retrieves controlled data, calls a tool, invokes an enterprise system, generates a regulated communication, modifies a record, triggers a workflow, or produces output that requires review, approval, or auditability. Effectful actions are what the Gateway authorizes and the Event Stream seals. Reasoning the model does in its own context is not effectful; the moment it reaches outside that context, it is.

What it is

A control plane, not a wrapper.

AlphaBitCore sits between the AI your enterprise builds and the systems that AI actually touches. Every model call, every agent action, every tool invocation routes through one place — the Gateway — where identity, scope, authority, and intent are checked before anything runs.

What's different from a typical governance layer is what comes out the other side: not a log entry, but a Proof of Execution. A cryptographically sealed certificate that binds who, under what policy, did what, with what effect, and lets you replay the execution deterministically from its event stream.

That single property — proof at runtime instead of logs after the fact — is what changes how audit, regulation, and risk-review actually work.

How it fits

Where the Control Plane sits in your stack.

You don't replace your model vendor, your cloud, or your data platform. The Control Plane is the governed path between your AI callers and the systems your AI actually affects.

Callers
Internal apps, agents, copilots, RPA, human-in-loop tools.
Speak to the Control Plane over a single SDK / HTTP contract.
Control Plane
Gateway · Runtime · Event Stream · Envelope
Policy, enforcement, proof — once, here.
Models & tools
Frontier LLMs, fine-tunes, vector stores, internal services.
Invoked only via the runtime. The Control Plane governs the invocation, not the model.
Systems of record
CRM, OMS, ticketing, data warehouse, audit store.
State changes are effects of a governed execution. Every effect is tied to a proof.
Disambiguation

What the Control Plane isn't.

The Control Plane shares surface area with several adjacent categories. Here's how it differs — so buyers place it on the right shelf and stakeholders don't waste cycles on the wrong comparison.

Not an agent framework.
Agent frameworks help you build an agent. The Control Plane governs execution across every model, agent, tool, skill, and workflow in your firm — frameworks and home-grown orchestrators included.
Not just an orchestration layer.
Orchestration dispatches work. The Control Plane enforces and proves policy at runtime while it dispatches — so the dispatch itself becomes part of an auditable chain.
Not observability.
Observability describes what happened after the fact. The Control Plane governs what happens, refuses what shouldn't, and produces a cryptographic proof of what did.
Not governance middleware.
Policy isn't advisory here. A denied execution produces zero state change and a sealed denial event. The policy engine is the thing that refuses bad behavior, not a description of it.
Not a compliance wrapper.
Compliance is a buying wedge, not the entire product story. Enforcement, auditability, and proof are infrastructure for any serious enterprise use of AI — regulated or not.
Next

See it against your stack.

A 30-minute walk-through mapped to your current model and tool inventory, policy surface, and audit pain.