Replit AI
Replit AI is an AI-powered coding platform that turns natural language into apps and websites, integrated into the Replit development environment
Managed memory and context layer for AI agents
Synap is a serious entrant in the crowded agent memory space alongside Mem0, Zep, and Letta, and its pitch of every capability on every plan with tiers only by volume is buyer-friendly. Published benchmark scores are strong, but they come from the vendor harness, so run your own evals before switching. The engine is closed source and cloud-managed, with on-prem only on Enterprise. The 19 dollar Starter price is a launch offer against a 49 dollar list price. Category is coding as the nearest fit for developer infrastructure.
Facts & pricing last checked October 2026. How we review
Maximem Synap is a managed memory layer for AI agents that ingests conversations, builds structured graph memory, and serves fast, relevant recall through SDKs for 20-plus agent frameworks.
Maximem Synap addresses a common agent problem: every conversation starts from zero. Synap runs as a fully managed cloud service with client SDKs, so developers ingest conversations and documents, and Synap extracts structured knowledge into graph memory and serves it back at retrieval time. Teams do not need to run or tune a vector database, reranker, or retrieval pipeline. The service offers fast, hybrid, and accurate retrieval modes, agentic compaction, anticipatory retrieval, consolidation, A2A protocol support, REST and WebSocket APIs, webhooks, and custom memory schemas, and all plans get every capability, with tiers differing by volume and support level. It integrates natively with more than 20 agent frameworks including LangChain, LangGraph, LlamaIndex, CrewAI, Google ADK, AutoGen, OpenAI Agents, Semantic Kernel, Haystack, Pydantic AI, and the Claude Agent SDK. Synap launched on Product Hunt on September 24, 2026. Maximem publishes its own benchmark harness and claims leading LongMemEval and LoCoMo scores; buyers should validate on their own workloads. The memory engine is not open source, though Enterprise plans list an on-premise option.
Maximem Synap is a managed memory layer for AI agents with strong published benchmarks, 20-plus framework integrations, and every feature on every plan.
Maximem builds memory infrastructure for AI. Synap serves developers building agents, while a sister product, Maximem Vity, offers private cross-app AI memory for individuals.
The company publishes research on agentic context management and an open benchmark harness, and launched Synap on Product Hunt in September 2026.
Synap provides ingestion, structured knowledge extraction, graph memory, three retrieval modes, agentic compaction, anticipatory retrieval, consolidation, A2A protocol support, REST and WebSocket APIs, webhooks, and custom schemas.
Plans add audit trail retention, BYOK model keys, and support levels as they scale, and Enterprise includes unlimited agents and an on-prem option.
Developers and startups building AI agents and assistants that need persistent, accurate memory without running retrieval infrastructure.
AI engineers integrating memory into agents.
Engineering leads and CTOs at AI startups.
Agent framework and LLM developer communities.
An AI startup running production agents that wants reliable long-term memory without building and tuning a RAG pipeline.
No funding information found in public sources as of this review; verify before publishing.
It is a managed memory and context layer that lets AI agents remember users, facts, and past conversations.
No. The memory engine runs as a managed cloud service. The SDKs are clients, and Enterprise plans list an on-premise option.
More than 20, including LangChain, LangGraph, LlamaIndex, CrewAI, Google ADK, AutoGen, OpenAI Agents, Semantic Kernel, and the Claude Agent SDK.
Yes. A free tier with 12,500 credits per month is available with no card required.
Maximem claims higher LongMemEval and LoCoMo scores and full features at its entry tier, but you should validate on your own data.
Side-by-side pages for pricing, features, and best-fit use cases.
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