Context & memory
Maintain working context, memory, and enterprise knowledge so long-running work stays coherent.
Cortexa home: M3.3 Collector + M4 Fabric
Enterprise AI infrastructure
Route signals. Apply gates. Close the loop.
Cortexa wraps a changing intelligence core in a calm control layer that screens every request, enforces policy, and returns trustworthy results.
Zero-trust policy screen
Live signal telemetry
Human-in-the-loop gates
// HARNESSSIGNALS
LIVE
CORE
SIGNAL
request#4821
POLICY
gate: pass
LOOP
closed · 3 gates
AUDIT
signed · trace
The model
Probabilistic intelligence
Reasons, generates, and produces language. It can be swapped as models evolve, but it does not provide enterprise control by itself.
The Cortexa harness
Enterprise execution layer
Manages context, routes models and tools, enforces policy, captures evidence, and verifies outcomes for reliable enterprise execution.
Six pillars
Everything production AI needs beyond the model.
Each harness pillar has a concrete home in Cortexa rather than being treated as a bolt-on feature.
Orchestration & tools
Route calls, validate parameters, and connect APIs, tools, databases, and workflows safely.
Cortexa home: M3.2 Orchestrator + M1 Nexus
Security & governance
Apply policy, approval gates, identity context, and risk controls directly in the execution path.
Cortexa home: M2 Govern
Observability & evaluation
Capture traces, evidence, scoring, and evaluation data so enterprise AI is auditable and measurable.
Cortexa home: M5 Signal
Model-agnosticism
Route across LLMs, SLMs, providers, and owned models without redesigning the control layer.
Cortexa home: Reasoning Layer + M6 DomainLM
Execution reliability
Continuously verify execution, detect errors, and ensure the system reaches a reliable completion state.
Cortexa home: M3.9 Reflector
How Cortexa is assembled
A control plane around a changing core.
Cortexa separates configuration and policy from runtime decisioning while keeping governance and reliability structurally embedded.
Management plane
Context, memory, application configuration, and enterprise controls.
Control plane
Orchestration, policy injection, routing, and runtime decision controls.
Cognitive engine
Reasoning, model selection, tool interaction, and enterprise knowledge.
// HARNESS CONTROL PLANE
ingress
route
gates
policy
core
infer
loop
audit
3
GATES
1
CORE
∞
TRACE
Inline governance + always-on reliability
M2 Govern applies policy across execution stages while M3.9 Reflector closes the loop.
Where the harness creates value
Built for enterprise AI that must operate, not just demo.
01 / AGENTS
Enterprise agents
Govern tool use, state, context, and task completion across long-running agent workflows.
02 / MULTI-MODEL
Multi-model AI
Route across LLMs and SLMs while keeping one consistent enterprise control layer.
03 / REGULATED
Regulated AI
Apply inline policy, evidence capture, approval gates, and auditability.
04 / KNOWLEDGE
Enterprise knowledge
Maintain governed context and memory across retrieval and enterprise systems.
05 / FINOPS
AI cost & routing
Choose fit-for-purpose models and paths rather than sending every request to the largest model.
06 / RELIABILITY
Agent reliability
Detect failures, evaluate outcomes, and close execution loops before completion.
07 / PRIVATE
Private AI
Support owned models and private deployment constraints without losing control.
08 / PLATFORM
AI platform layer
Give multiple applications a shared layer for policy, routing, evidence, and runtime intelligence.
Agents, gateways, and harnesses
Different layers. Different jobs.
Agents and AI gateways are important parts of the enterprise AI stack, but neither replaces the cross-cutting control and execution role of an Enterprise Harness.
AGENT
Goal-oriented worker
- —Plans and reasons
- —Calls tools
- —Performs tasks
- —Operates within a workflow
GATEWAY
Access & traffic layer
- ✓Routes model requests
- ✓Authentication and quotas
- ✓Endpoint abstraction
- ✓Usage and traffic controls
Enterprise harness
Cross-cutting enterprise execution and control layer
Context + memory + orchestration + tools + policy + governance + observability + evaluation + model agnosticism + closed-loop reliability.
What enterprises get
A durable layer between applications and models.
Context
Persistent & governed
Execution
Orchestrated & reliable
Governance
Inline, not bolted on
Models
Provider-agnostic
Evidence
Traceable & auditable
Reliability
Closed-loop verification
Enterprise control
Policy-aware
Longevity
Outlives model churn
Cortexa Enterprise Harness
Your model may change. Your control layer should not.
See how Cortexa sits between enterprise applications, agents, tools, retrieval systems, and any LLM or SLM to provide consistent context, governance, observability, and reliability.