Research
Technical notes on institutional memory, investment intelligence, and the systems behind Recallr.
A Deal Library Should Change the Next Deal
If your archive only helps people retrieve old files, it is not yet an investment system.
Your Firm Has a Memory Problem
The cost is not finding a document. It is losing the reasoning that made the document matter.
AI Is Not the Strategy. Better Investment Decisions Are.
A practical look at where AI earns its keep in private equity, and where it does not.
Why RAG Isn't Memory
RAG retrieves static document chunks. Private capital memory needs to understand what changed, when, and why across deals, diligence, and decisions.
How We Scored 97.5% on LongMemEval
A technical breakdown of the temporal memory architecture behind Recallr's private-capital decision graph and benchmark performance.
The Hidden Cost of Naive Chat History
Why re-sending institutional history as context becomes expensive fast, and how structured memory keeps private-capital AI workflows efficient.
Recallr vs Mem0: Temporal Memory Benchmark Comparison
A benchmark comparison of Recallr and Mem0 across accuracy, temporal reasoning, and latency, framed for high-stakes institutional memory.
Recallr vs Zep: Which Memory Layer Wins on Temporal Reasoning?
How Recallr and Zep compare on temporal reasoning, versioned knowledge graphs, and the requirements behind institutional memory systems.
Best AI Memory Layer in 2026: Full Comparison
A data-driven comparison of memory layers, with emphasis on temporal reasoning, institutional knowledge, and private-capital AI workflows.