AXIO Cortex / Console
LAB-01 · Implemented · active development · Last reviewed 29 August 2026.
An execution environment designed to run locally first, joining model routing, durable memory, bounded tool use, approval gates and verification that produces evidence in one console under operator control.
The question
How can an AI system retain useful context, choose the right model and use real tools without confusing capability with authorization?
AXIO’s approach
Cortex treats an AI response as one step inside an auditable operating loop: retrieve context, select a bounded capability set, execute under policy, verify the result and preserve durable evidence.
Highlights
- Four operating modes: Chat, Cowork, Code and the isolated RevRec finance workflow.
- Local Ollama inference with configured cloud escalation when the task and policy allow it.
- Postgres/pgvector as the canonical semantic store when enabled, with resilient local mirrors and fallback.
- Tools from the registry exposed to the model in bounded subsets selected for the current task rather than one unrestricted catalog.
How it works
- Intent — A deterministic classifier identifies planning, research, coding, debugging, testing or file operations. Control: Classification is inspectable and can be tested independently of the model.
- Route — The runtime chooses the configured local or cloud model and assigns a task budget. Control: Local only operation cannot silently fall back to cloud.
- Recall — Relevant session facts, semantic lessons and approved project context are recalled before execution. Control: RevRec remains isolated while general modes can share approved recall.
- Tools — Only a bounded subset of registered tools is visible for the current step; hidden tools require an explicit request. Control: Availability never overrides path, approval or consequence policy.
- Execute — The agent performs the smallest authorized action and records observations after every tool call. Control: Consequential actions require human approval and failures must change the next approach.
- Verify — Outputs are reopened, tested or checked against evidence for the current task before completion. Control: A generated file or passing registry check is not treated as proof of working behavior.
- Remember — Sessions, facts, lessons and trajectories are consolidated into the appropriate memory tier. Control: Durable local recovery protects work when the primary database is unavailable.
What AXIO delivers
AXIO applies the Cortex operating pattern to organizations that need private, governed AI execution connected to real business tools.
- Architecture and model routing blueprint for the client environment.
- Memory, tool authorization and human approval design.
- Pilot implementation with observable verification and rollback criteria.
Evidence & maturity
- Verified in code — Resilient memory tiers: The current codebase implements Postgres/pgvector retrieval, a Chroma mirror, local JSON durability and keyword fallback.
- Verified in code — Bounded dynamic tool routing: The router classifies tasks and reveals a limited capability set with an explicit request mechanism for hidden tools.
- Variable by checkout — Tool inventory: The registry changes as native capabilities are added. AXIO therefore verifies the live registry before publishing a count.
- Depends on configuration — Primary memory backend: Postgres is the system of record when that backend is active; ad hoc runs can intentionally use the local fallback.
Safeguards
- Human approval for consequential, external or irreversible actions.
- Memory policy for each mode with RevRec context isolation.
- Durable outbox and replay behavior for temporary Postgres outages.
- Protection against repeated calls, repeated errors and no progress in loops.
- No public exposure of prompts, credentials, local paths or raw memory content.
Frequently asked questions
How can an AI system retain useful context, choose the right model and use real tools without confusing capability with authorization?
Cortex treats an AI response as one step inside an auditable operating loop: retrieve context, select a bounded capability set, execute under policy, verify the result and preserve durable evidence.
What does AXIO deliver in this engagement?
AXIO applies the Cortex operating pattern to organizations that need private, governed AI execution connected to real business tools. Typical deliverables: Architecture and model routing blueprint for the client environment; Memory, tool authorization and human approval design; Pilot implementation with observable verification and rollback criteria.
What is the current maturity of this work?
Implemented · active development. Verified in code: The current codebase implements Postgres/pgvector retrieval, a Chroma mirror, local JSON durability and keyword fallback.
Contact & resources
Founder & CEO: Michael Vega. Email: [email protected]. Phone: +506 6300 5688. LinkedIn: linkedin.com/company/axiostaging. GitHub: github.com/VegaBuildsAI. Machine-readable resources for agents and developers: llms.txt, OpenAPI specification, MCP manifest, and agent instructions.