Memory as Infrastructure, Governance & Identity for AI Agents

MAIGI eliminates redundant context reads, reduces AI agent costs by 90%, and guarantees consistency and compliance across concurrent agents.

Ready to Cut AI Agent Costs 90%?

Join enterprise teams using MAIGI to reduce token spend from $500K/year to $50K/year while guaranteeing agent consistency and compliance.

How MAIGI Works

Three core capabilities that solve the AI agent cost crisis

💾

Persistent Memory

Instead of reloading context every turn, MAIGI stores agent conversations in a PostgreSQL-backed memory layer. When agents request context, they get only the NEW data—everything else is deduplicated via content hashing and version control.

🔒

Multi-Agent Safety

When 10 agents read the same CRM record simultaneously, MAIGI guarantees ACID consistency. No race conditions. No conflicts. Built-in orchestration sagas handle distributed transactions across concurrent agents without data corruption.

📊

Complete Visibility

Every agent interaction is logged. Who accessed what data, when, and why. Full audit trail for compliance. Temporal queries let you ask "what was the state at 2pm yesterday?" Perfect for debugging and regulatory requirements.

Where MAIGI Makes the Biggest Impact

Real-world scenarios where multi-agent memory saves Fortune 500 companies thousands per month

🎯 Primary Market

Enterprise Sales Teams

The Problem: 10 sales agents simultaneously reading Salesforce CRM to qualify deals. Each turn reloads the full customer context (5000+ tokens). Multiply by 5 turns per conversation × 100+ daily conversations = massive token waste and stale data.

With MAIGI: First read loads full context. Subsequent reads get only new data. Agent 2 reading same customer pays zero token cost for already-loaded context.

Cost Today
$12K/mo
With MAIGI
$1.2K/mo
🚀 Quick Win

Customer Support Teams

The Problem: Support agents handling 10-50 message support conversations. Each message causes the agent to reload full ticket history + KB + customer profile. By message 20, context window is consumed, agent starts forgetting earlier messages.

With MAIGI: Agent sees full conversation history without token bloat. MAIGI deduplicates context across all 50 messages. Result: 95% first-contact resolution, 90% cost reduction.

Cost Today
$1.20/ticket
With MAIGI
$0.15/ticket

The Impact

Without MAIGI vs With MAIGI

❌ Status Quo

  • Full context loaded every turn
  • Redundant reads across agents
  • Token counts explode with turns
  • Race conditions on updates
  • No consistency guarantees
  • $500K+ annual token costs
Cost per conversation:
$0.50

✓ With MAIGI

  • MVCC deduplication
  • Session-aware versioning
  • Only new data fetched
  • Orchestration sagas
  • ACID consistency
  • $50K annual token costs
Cost per conversation:
$0.055
90% Cost Reduction
For one Fortune 500 company: $144,000/year savings

Frequently Asked Questions

Everything enterprise teams need to know

How is MAIGI different from vector databases?
Vector databases are designed for semantic search over embeddings. MAIGI is designed for agent-aware memory management with ACID guarantees. We focus on deduplication, multi-agent consistency, and cost reduction—not semantic search.
Does MAIGI work with my LLM provider?
Yes. MAIGI works with any LLM provider (OpenAI, Anthropic, open-source models, etc.). We're a memory layer, not an LLM integration. Your LLM makes requests to MAIGI for context, and we return deduplicated data.
What about data privacy and compliance?
MAIGI provides complete audit trails, session tracking, and compliance-ready logging. You can self-host on your infrastructure or use our managed service. Full SOC 2 compliance roadmap.
How quickly can we implement MAIGI?
Most integrations take 2-4 weeks. We provide Python SDKs, REST APIs, and detailed documentation. Your team integrates MAIGI into your agent framework—no major architectural changes needed.
Do you offer support and SLAs?
Yes. Enterprise customers get dedicated support, custom SLAs, and priority feature requests. Starter tier includes community support and documentation.