Recalld vs FastRecall
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Recalld compared with FastRecall
| Detail | Recalld | FastRecall |
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| What it does | The memory layer for AI Agents
| Context across AI models. Made for routers and multi-agent systems.
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| Stage | Growing
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| Founded | Not given
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| Based in | Not given
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| Pricing model | freemium
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| Pricing | Not given
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| Key features | - Long-term memory for AI agents
- Automatic fact extraction and reconciliation
- Curated recall retrieval
- Raw vector search capability
- Model Context Protocol integration
- Regional data residency
- End-to-end encryption
- Right to erasure
- Bring-your-own-key model support
- Recalld Chat assistant
| - Lightning fast context recall
- Free context retrievals
- Model-free context compaction
- Multi-model support
- FlashCompact intelligent context organization
- Model provider caching integration
- Persistent context across providers
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| What makes it different | - Curated recall uses 6.7× fewer tokens than raw search while maintaining accuracy
- Automatic fact updating and reconciliation without manual deduplication pipelines
- Verified on open benchmark maintained by independent company
- Native MCP server requiring no SDK or glue code
- GDPR-compliant by design with transparent data handling
| - No LLM-based compaction overhead
- Multi-model compatibility
- Inexpensive storage pricing
- Fast recalls with no retrieval fees
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ● no change since last check | 2 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 0 |
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| Citation Flow (Majestic) | 15 | 25 |
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| Referring domains (Majestic) | 10 | 27 |
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3 details filled in for both companies.
More alternatives to Recalld More alternatives to FastRecall