Kit for AI vs Zep
Zep is a long-term memory store for LLM applications. If you want an all-in-one, private and cheaper long-term memory for LLM apps that also converts documents, remembers, recalls and searches the web, Kit for AI is the better fit.
What Zep does well
Zep gives LLM apps durable conversation memory and a fast recall API, with good support for chat history and fact extraction.
Why teams choose Kit for AI
- Beyond conversation memory: Kit for AI turns your real documents — PDFs, Office files, URLs, scans — into a searchable, cited knowledge base, not just a chat-history store.
- Hybrid retrieval (vector + keyword, RRF-fused) with cross-encoder reranking and grounded citations, so answers are precise and traceable — not just fast recall of extracted facts.
- Local models keep your memory and documents private, and convert, remember, recall, search and skills all share one REST API and MCP server.
How Kit for AI is built
The difference isn't just scope — it's technique. Here's what drives more accurate, cheaper, more private answers.
Hybrid retrieval, not vector-only
Most memory and RAG tools rank passages by vector similarity alone, which misses exact terms and names. Kit for AI fuses dense vector search with keyword search using Reciprocal Rank Fusion, then reranks the shortlist with a cross-encoder — so the passage that actually answers the question lands first. Higher precision means fewer chunks in the prompt, and fewer tokens billed.
Grounded answers that cite — or decline
Every answer is generated only from your retrieved passages and cites the exact source. When your documents don't cover a question, the model says so instead of inventing an answer. No confident hallucinations, no untraceable claims.
Token-efficient ingestion
Sources aren't dumped in raw. PDFs, Office files, HTML, URLs and scanned images run through a conversion ladder — including vision-model OCR — into clean, structured Markdown. Clean input cuts token counts sharply versus raw extraction, and gives the model less noise to reason over.
Private by default
Answers run on our own models, so your documents and memories aren't sent to a third-party LLM. You get the retrieval quality without handing your corpus to OpenAI or Anthropic.
One surface, zero retrieval infra
Convert, knowledge bases, memory (remember/recall), web search and skills are one REST API, one MCP server, and a typed SDK. No vector database to run, no embedding pipeline to maintain, no chunking strategy to tune — it's managed end to end.
Feature comparison
| Feature | Kit for AI | Zep |
|---|---|---|
| Retrieval technique | Hybrid (vector + keyword) fused with RRF, then cross-encoder reranking | Vector similarity |
| Grounded, cited answers | Cites every source; declines when your docs don't cover it | Fact/graph recall |
| Document → clean Markdown / JSON | PDF, Office, HTML, URLs, images/OCR — token-efficient | Not included |
| AI OCR for scans & images | Vision-model OCR → structured Markdown | Not included |
| Retrieval infrastructure to run | None — no vector DB, embeddings or chunking to manage | Hosted memory infra you integrate |
| Local / private AI (no third-party LLM) | Runs on our own models | Hosted LLM (OpenAI/Anthropic) |
| Developer surface | REST API + MCP server + typed SDK | API only / limited |
| Agent memory (remember / recall) | Built-in, deduplicated, semantic | Core product |
| All-in-one (convert → KB → memory → skills → search) | One platform, one API | Memory infra |
| Starting price | Free tier · Pro $9/mo | Infra/usage pricing + LLM cost |
Pricing
Zep prices around hosted memory infrastructure you wire into your own LLM stack. Kit for AI folds memory into an all-in-one $9/mo plan — conversion, cited knowledge bases, memory and search, answered on private models, no separate LLM bill.
FAQ
- Is Kit for AI a Zep alternative?
- For durable memory, yes — remember/recall persist facts across sessions with semantic retrieval and deduplication. Kit for AI goes further by turning your documents into a cited knowledge base and adding web search and conversion, all on one API and MCP.
- How does retrieval compare to Zep?
- Kit for AI fuses vector and keyword search with RRF and reranks with a cross-encoder, then grounds and cites the answer — favoring precise, source-traceable results over recall speed alone.
- Do I still need my own LLM and vector store?
- No. Kit for AI answers on our own local models and manages retrieval end to end — there's no vector database, embedding pipeline, or external LLM to wire up and pay for separately.
- Is my data private?
- Yes — memory and documents are answered by local models and aren't sent to a third-party LLM.
Switch to the all-in-one AI toolkit
Convert, build a knowledge base, remember, recall, run skills and search — one API, private models, from free.