Built for agents. Built for robots.
The same memory engine behind coding agents, support desks, research swarms and warehouse fleets. Start from a reference architecture.
- TutorialsEngineering
Coding and DevOps agents
Codebase conventions, “already tried that” bug history and incident runbooks that survive every session.
- TutorialsVertical AI
Support, sales and research agents
Account history, preferences and past resolutions recalled the moment a conversation starts.
- TutorialsRegulated
Finance and legal agents
Every fact with a source and a validity window, and every change reviewable on a branch before it lands.
Software agents
Overview →- Autonomous Coding Agents
- Maintains codebase conventions, previous commit rationale, and “already tried that” bug histories across daily IDE sessions.
- Multi-Day Research Swarms
- Preserves verified claim registries, citation graphs, and conflicting hypothesis notes across long-running autonomous sweeps.
- Algorithmic & Financial Agents
- Tracks macro indicators, execution fill anomalies, and risk regime state across continuous 24/7 market monitoring.
- Customer Operations & Support
- Surfaces past ticket resolutions, enterprise account SLAs, and user satisfaction history instantly upon ticket creation.
- Multi-Agent Swarm Coordination
- Shared transactional workspace where planning, execution, and review agents share state with zero desynchronization.
- Healthcare Clinical & EHR Agents
- Maintains longitudinal patient histories and drug interaction contraindications with per-patient isolation and a full audit trail.
Robots
Overview →- Warehouse & Logistics AMRs
- Dynamic aisle obstacle mapping, waypoint rerouting, and real-time fleet map synchronization across hundreds of mobile robots.
- Industrial Automation & Grippers
- Retains fine-motor grasping parameters, surface friction coefficients, and bin sorting failure recoveries.
- Autonomous Inspection Drones
- Stores 3D volumetric point clouds, flight telemetry, and infrastructure structural fatigue logs across successive flights.
- Humanoid & Bipedal Robots
- Preserves terrain locomotion adaptations, human interaction etiquette, and complex multi-step choreographies.
- Autonomous Vehicles & AGVs
- High-payload vehicle haul-road conditions, blind-spot object tracking, and fleet-wide route hazard propagation.
- Agricultural & Field Robotics
- Offline local edge execution on tractors and harvesters for soil moisture and crop yield mapping with cloud synchronization.
Every tutorial, by team.
Customer Support Agents
Enterprise support agents deploy multi-turn interactions for consumer brands, resolving complex logistics queries rather than repeating rigid decision trees.
Log in to Sierra AI Admin Console -> Settings -> External Memory Providers.
Click "Add Custom Data Provider" and select Model Context Protocol (MCP).
Enter your Hosted Axonio MCP Endpoint: https://api.axonio.xyz/api/v1/mcp.
Paste your Axonio Secret Key (CLAWDB_API_KEY) and map Session ID to namespace: customer_{id}.
How to Connect Axonio Memory to Sierra AI & Zendesk
Copy and paste this config file into your target tool (Sierra AI & Zendesk)
{
"memoryProvider": "clawdb-mcp",
"mcpEndpoint": "https://api.axonio.xyz/api/v1/mcp",
"apiKey": "claw_sec_live_948201...",
"namespaceTemplate": "customer_{user_id}",
"autoDistillEpisodes": true
}Exact Installation & Enablement Steps:
- Log in to Sierra AI Admin Console -> Settings -> External Memory Providers.
- Click "Add Custom Data Provider" and select Model Context Protocol (MCP).
- Enter your Hosted Axonio MCP Endpoint: https://api.axonio.xyz/api/v1/mcp.
- Paste your Axonio Secret Key (CLAWDB_API_KEY) and map Session ID to namespace: customer_{id}.
Use-case questions.
Can software agents and physical robots share the same memory workspace?
Yes. A human operator using a conversational AI agent and an autonomous warehouse robot can read and write to the same Axonio workspace, enabling software agents to monitor and command physical fleets in real time.
How does Axonio run on low-power edge hardware?
The engine embeds into edge hardware (ARM64 and x86) with a small memory footprint and runs fully offline, with local-benchmark retrieval under half a millisecond.
Where do I find code examples for my specific use case?
Check our comprehensive documentation and GitHub repository for starter templates across LangChain, CrewAI, ROS2, NVIDIA Isaac Sim, and OpenAI Agents.