Running Cogni as a service, Agent Memory Knowledge Connectors

Cogni Agency Implementation, Building Retainer-Ready AI Memory Systems

Learn how to architect and deliver Cogni-powered memory systems for your clients' AI agents and automation workflows. This course covers entity-graph design, spreading activation optimization, multi-agent memory sharing, and pricing models for recurring revenue through memory seat licensing and usage tiers.

Open the decision record for Cogni

What does running Cogni for clients commit you to?

Published figures for this service. Blank fields are not published.

Monthly tool cost
Free tier available; paid tier starts at $20/month (vendor cost)
Time to first value
Hours
Payback
Not modeled
Guided implementation
8 hours

Is Cogni worth running as a client service?

The evidence supports Cogni as a technically capable memory layer for AI agents, but its commercial viability for agencies depends on client demand and delivery efficiency, which are not yet proven.

An agency-fit judgement for reselling this service. It is separate from the tool description on the decision record.

Before you start

What has to be in place before the first client engagement.

Tools and subscriptions

  • Cogni MCP server
  • MCP-compatible client (e.g., Claude, Cursor, VS Code)
  • Claude API access
  • OpenAI API access
  • Google AI API access

People and inputs

  • Entity-graph data modeling skills
  • Integration with LLM APIs
  • Testing and QA procedures

Included with the course

7 working documents for delivering this service.

  • Cogni Entity-Graph Design Worksheetworksheet
  • AI Agent Memory Retainer Pricing Templatetemplate
  • Spreading Activation Query Optimization Checklistchecklist
  • Multi-Agent Memory Architecture SOPsop
  • Cogni Pro vs Team Plan Client Comparison Guideguide
  • Memory Graph Audit and Pruning Workflowsop
  • Cross-Vocabulary Retrieval Testing Checklistchecklist

Listed by name. These documents are not yet published as individual downloads.