Memorable GTM brain
Memorable gives AI agent builders procedural memory that captures successful workflows and retrieves them for similar tasks.
category
AI agent procedural memorymarket profile
- text: Agents repeatedly solving similar tasks can waste tool calls and tokens reconstructing steps; procedural recall targets this repetition.
- text: Dedicated memory layers also compete with general fact memory, graph frameworks and agent-native persistence.
personas
- title: AI Agent Engineerpains:
- Agents rediscover known workflows across runs
- Must debug whether recalled steps were actually successful
- title: Engineering Manager, Developer Productivitypains:
- Repeated coding agent work drives token and execution cost
- Needs to evaluate memory improvements across real tasks and existing harnesses
- title: AI Platform Leadpains:
- Agent traces may contain sensitive information
- Needs explicit control over what is recorded and sent
icp
- text: Software teams deploying coding or workflow agents that repeatedly execute similar multi-step tasks.
- text: Agent platform builders with traces and a measurable baseline for tool calls, task completion and token cost.
message pillars
- text: Reuse the procedures behind successful agent runs.
- text: Turn traces into compact workflows without unsuccessful branches.
- text: Connect recalled workflows into plans for multi-part tasks.
objections
- objection: Will it work with our agent harness?response: The site lists curated integrations and a JSON trace path for other harnesses; test your own traces.
- objection: Does memory expose complete agent transcripts?response: The site says transcripts are not sent and recording requires explicit enablement; verify the actual data flow for your deployment.
- objection: Do savings hold for our workload?response: Benchmark similar tasks with and without recall, including failures and memory overhead.
competitors
- name: Mem0why: Provides agent memory extraction and retrieval through an SDK and hosted service.
- name: Zepwhy: Offers graph-based memory and retrieval for agents.
- name: Lettawhy: Provides stateful agents with long-term memory capabilities.
keywords
- agent procedural memory
- AI agent workflow memory
- coding agent memory
- agent trace reuse
- graph memory for AI agents
- reduce agent token usage
voice
- developer-oriented
- measurable
- technical and direct
signals
- text: An engineering team runs repeated coding or support workflows through agents and tracks token costs.
- text: A team is evaluating persistent agent memory or instrumenting traces for agent evaluations.
stack
- Claude Code
- Codex
- OpenCode
- gbrain
pricing
model: unknown
motion
hybridchannels
- developer documentation
- YC Launch
- website
confidence
mediumFounders
- name: Nikhil Krishnaswamytitle: Founder/CEOrole: CEObio: CS @ Stanford Building navigation for agents @ Memorable nikhil@memorable.sh
- name: Advaiyt Sanetitle: Founder/CTOrole: CTObio: CS @ CMU '29 Creating Memorable, turning agent reasoning into graph search.