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AI Tool Comparison

Hatz AI vs Letta

A side-by-side breakdown to help you pick the right tool for your workflow.

Hatz AI logo

Hatz AI

Build and deploy AI agents for research, file analysis, HR, and RFP responses via natural language, with multi-LLM access in one SOC 2-compliant interface for SMBs and MSPs.

Agents
paid
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Letta logo

Letta

Build agents that actually remember: facts, preferences, and past interactions persist across every session without manual context management.

Agents
freemium
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Bottom Line

Last reviewed: August 2026

Hatz AI and Letta both sit in Agents, but they're built around different use cases within it. Hatz AI runs on a paid-only plan while Letta runs on a freemium model, which alone may settle it if budget or a free tier is a hard requirement. Letta carries the higher rating (4.4 vs 4.3), but a gap that size rarely overrides a real workflow fit on its own.

Choose Hatz AI if…

Best for managed service providers and agencies who want to resell branded AI assistants under their own name, and its edge is a genuine white-label model that lets a reseller present AI capabilities without building infrastructure from scratch. Built specifically for agencies and resellers, not a fit if you're not already serving clients this way.

Choose Letta if…

Best for developers building agents that need to remember and update facts across arbitrarily long interaction histories, and its edge is manages its own memory tiers and decides what to retain or summarize, more reliable than an ad-hoc RAG memory hack. A genuinely more solid approach to agent memory than manual context management, per-step cloud pricing adds up for memory-heavy agents.

AttributeHatz AILetta
CategoryAgentsAgents
Pricingpaidfreemium
Pricing DetailCredit-based plans, tailored to company sizeOpen source / Free (Letta Cloud from $0.02/step)
Rating4.34.4

Key Features

Hatz AI

  • White-label AI assistants
  • Custom agent apps
  • Client management
  • Secure data handling

Letta

  • Three-tier memory architecture: working, recall, and archival
  • Self-directed memory management: agents decide what to store
  • Cross-session persistence with no manual prompt engineering
  • REST API and Python SDK for embedding agents in applications
  • Agent builder UI for configuring memory and persona
  • Open-source core with managed Letta Cloud option

Pros

Hatz AI

  • Great for resellers
  • White-label control
  • Security focus

Letta

  • Solves long-term memory without external memory databases or prompting tricks
  • Open-source core means full control over data and deployment
  • Framework-level memory is more reliable than ad-hoc RAG approaches

Cons

Hatz AI

  • Agency-focused (not consumer)
  • Pricing for businesses

Letta

  • Memory management adds latency compared to stateless agents
  • Cloud pricing is per-step, complex agents with many memory reads get expensive
  • Steeper learning curve than simpler stateless frameworks

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