Memory layer for enterprise AI agents
Your agents stop starting from zero every day. They know your customers, your decisions, your processes, your team's institutional knowledge. They act on it.
For engineers: read the full architecture.
Why this matters
They don't know your customers, your decisions, your processes, or your team's institutional knowledge. So they hallucinate, redo old work, and embarrass you in front of clients.
Today's memory tools (mem0, Letta, LangMem) solve this for chatbots, not for the way your enterprise actually works. Vector stores and RAG search what already exists. Glean and Notion AI search what's already written.
Mycelium is the memory layer underneath: the substrate your agents read from, write back to, and get smarter on, across every team and every tool you already use.
Agent personalization
mem0, Letta, LangMem, Zep
Tuned for chatbot memory at the conversation layer. Different category.
Retrieval
Pinecone, Weaviate, RAG frameworks
Search a corpus that already exists. Mycelium is upstream of them.
Indexing & chat-on-docs
Glean, Notion AI, Coda AI
Search what's already written. Mycelium is the substrate the rest of the stack reads from and writes back to.
How it works
Each component has a plain-language job. The technical detail underneath is for the engineer on your buying committee.
Memory · Routing · Skills · Learning · Portability
Your enterprise's context lives in plain text files you own. Auditable. Version-controlled. Readable by a human or a model.
EngineerMarkdown over Git, typed-memory schema, no proprietary database lock-in.
MEMORY
Agents find the right context without scanning everything. Answers can be scoped to what was true on a given date.
EngineerRESOLVER pattern with bi-temporal lookup over the typed graph.
ROUTING
Reusable instructions your agents follow. Composable, testable, swappable. Not a prompt library.
EngineerEach skill ships with a single SKILL.md spec, an entry contract, and a reproducible side effect.
EXECUTION
Every refined answer makes the next one better. The system gets smarter without retraining a model.
EngineerClosed-loop write-back discipline. Episodic memory promotes to procedural in seconds.
FEEDBACK
Swap Claude for GPT for Gemini for Llama for whatever's next. Your memory stays put.
EngineerSeparation of context from compute. Substrate is portable; runtime is configurable per workflow.
PORTABILITY
Connectors
Connectors normalize external context into the memory layer. The roster covers the systems your operators already work in every day.
Shipping next
Salesforce
CRM
Microsoft 365
Email + Docs + Teams
Confluence
Wiki
Live in production
Slack
Messaging
GitHub
Code + issues
Notion
Docs + wiki
Linear
Issues + projects
Gmail
Messaging
On the roadmap
ServiceNow
ITSM
Workday
HR + Finance
SAP
ERP
Box
Files
Google Workspace
Email + Docs + Drive
Snowflake
Data warehouse
Databricks
Data + ML
Need a connector that isn't here? Naming it on a pilot scope call adds it to the build queue.
What ships
Every line below is shipped, in production, today. Click through to /technical for the engineering detail.
A queryable layer of decisions, exceptions, people, projects, and policies. Answer 'what did we decide about X' in one query, not in three meetings.
Six connectors live today: Slack, GitHub, Notion, Linear, Gmail, WhatsApp. Three enterprise connectors shipping next: Salesforce, Microsoft 365, Confluence.
A merged pull request becomes a workflow your team can reuse. A resolved Slack thread becomes a memory entry your agents can look up. No manual SOP-writing.
What did the team know on the day the audit observation happened? What did the policy actually say last quarter? Both questions, one query.
Every refined answer, every approved decision, every resolved exception writes back into the substrate. The system improves without retraining a model.
Production grade
Plain-language guarantee on top, the technical detail in mono underneath, for the security engineer reading along.
Your data stays your data.
EngineerMulti-tenant JWT auth scoped per tenant. No cross-tenant reads, no shared state.
Compliance can answer who-did-what-when.
EngineerFull audit log: actor, tenant, timestamp, source on every read, write, and synthesis.
Real-time event stream for live integrations.
EngineerPer-tenant Server-Sent Events. Subscribe to ingestion, synthesis, and decision events.
Untrusted networks can't trigger actions in your system.
EngineerHMAC-validated webhooks. Async retry queue with exponential backoff. Dead-letter folder per tenant. Admin-only replay.
Reliability you can verify in writing.
EngineerProduction-tested for 13 months. Every release passes 59 automated checks before it ships. End-to-end integration test on every code change.
Production-tested 13 months · 59 automated checks per release · End-to-end integration tested on every change
Security & Compliance
If you have a Vendor Risk Management questionnaire on your desk, this is the section to send to your security team.
On the calendar. Audit window and current readiness state available on request from security@myceliumai.co.
US and EU options on Vercel + AWS-backed deployments. Region pinning configurable per tenant on the productized runtime.
Multi-tenant managed runtime, single-tenant managed runtime, and on-premise install. Single-tenant and on-premise unlock with the Enterprise Pilot tier.
Enterprise tier includes a contractual SLA. Uptime target and response-time tiers are negotiated per pilot scope and named in the engagement letter.
Permissions scoped per tenant, per workspace, per resource. Read, write, and synthesis are independent. Audit log carries the actor identifier on every event.
Default 12 months in the managed runtime, extendable to 7 years for SOX or HIPAA-adjacent buyers. Audit exports are gzipped JSONL signed with a tenant key.
TLS 1.3 in transit. AES-256 at rest. Per-tenant encryption keys available on the Enterprise Pilot tier; key rotation via the admin API.
Reach security@myceliumai.co. We acknowledge within one business day, triage within five, and credit researchers in the public CHANGELOG.
What you build on it
These are the kinds of workflows the substrate makes routine. Each one depends on memory that survives session boundaries, tools, and time.
An agent drafts your sales outbound knowing every Salesforce note about the prospect, every conversation your team has had with their company in the last year, and the last successful close in the same segment. Your rep edits one sentence and sends.
An agent prepares your SOC 2 audit binder by pulling HR records, IT tickets, and compliance policies into a single document your auditors approve in one pass. It answers what was true on the audit observation date, even if the policy has since changed.
Workday and ServiceNow are on the roadmap; the workflow runs end-to-end once those connectors ship.
An agent onboards a new hire by surfacing every decision, every relevant Slack thread, and every meeting note from the team they're joining. They walk in on day one knowing what was already tried and why.
Where Mycelium sits
Most of the systems below solve a real problem. None of them solve the memory-layer problem. The columns are what an enterprise buyer actually needs; the marks identify systems that publicly satisfy each one.
| Your data stays portable | Tracked in version control | Multi-tenant safe | Audit-logged | Swap models without rebuilding | Open core | Enterprise connectors | Answers are version-aware | |
|---|---|---|---|---|---|---|---|---|
| Mycelium | ||||||||
| mem0 | · | · | · | · | · | · | ||
| Letta | · | · | · | · | · | · | ||
| LangMem | · | · | · | · | · | · | · | |
| Pinecone | · | · | · | · | · | · | · | |
| Weaviate | · | · | · | · | · | · | ||
| Glean | · | · | · | · | · | |||
| Notion AI | · | · | · | · | · | · |
Verified against each vendor's public documentation as of 2026-05. Corrections to security@myceliumai.co.
Proof
The memory layer did not start in a clean room. It ran across an active corporate-events startup with Accenture as anchor client, an AI consulting practice with paying installs, and 5,000+ documents spanning customer, project, and decision contexts.
5,000+
documents
Files spanning customer, project, and decision contexts. Tracked in version control, queryable as a knowledge graph.
Accenture
anchor client
Active corporate-events engagement running on the substrate. The work it held while it ran is not a demo.
Multi-business
substrate
AI consulting practice with paying installs runs on the same substrate. Two operating businesses, one memory layer.
Production
tested
13 months under real load before the productized runtime existed. The hardest possible test environment.
We dogfood: the same substrate also holds the founder's twelve years of journals and two long-form writing projects. If it survives that, it survives your sales floor.
Co-brand
Andrés Bilbao's program is filling the first commercial cohort: $3,000 per seat, 60 seats targeted, 16 hours live plus 8 hours of office hours, every participant leaving with a personal install of the substrate by Session 1.
Design partners
Operators using the memory layer today, in production, in their own businesses.
“I've spent over 10 years building systems to run my life and my companies. I've fired more productivity tools than employees. My verdict on Adelaida's system after testing it: someone with no technical background in software can reach more than 85% of the efficiency tech-fluent people operate at today, without writing code and without getting locked into a vendor. You operate the capability yourself, you don't rent it.”
Sebastian Gallo
Co-Founder, Torre
Founder, newshare now
“I installed AI Growth with an empty vault. Today it's the operating system of three companies. In less than two weeks: almost 11,000 files. 58 people in a CRM with full history. 143 Granola transcripts auto-imported. 1,300+ WhatsApp threads logged. More than an Obsidian template, it's an architecture. I built 11 Claude Code skills and 400+ scripts on top of that base.”
Danny Bravo
Founder, Hardcore AI by 30X
Tribu iA · Rewired
“The system Adelaida built is an integral and highly effective solution. It goes beyond being a simple tool: it lets you automate both personal life and the office consciously. It's fully accessible to people without technical or programming knowledge.”
Andrea Liévano
Founder & CEO, PRPARATODOS
Author, Visibilidad Infinita (Editorial Planeta)
“I don't know how I'd function today without the second brain Adelaida helped me build. It understands my background and my goals, and with all of that helps me create proposals, structure internal improvements in my business, and even coach me. It's a before and after.”
Luisa Lafaurie Cabal
Founder, Luisa Postres
Co-Owner, Student Travel Center
“The more technology there is, the more human we must become. If a machine can do everything, and do it well, like the brain Adelaida built, why not use it? It's life-changing. Now I have more time for what only a human can do.”
Camila Fierro
Founder, Alción
Global Shaper, World Economic Forum
Pilot pricing
Both tiers leave you with a working memory layer. The Enterprise tier is the version that clears Vendor Risk Management.
AI-Native Sprint
$25K – $75K
60-day install
Scale-ups with an AI team adopting agents internally and a small connector surface.
Procurement-grade
$150K – $500K
90-day install + 12-month runtime
Fortune 100 buyers with an existing AI initiative, real Vendor Risk Management process, and a named integration scope.
How a pilot runs
Every pilot follows the same shape. Pilot Lite compresses the timeline; Enterprise Pilot adds dedicated engineering through Week 12.
Week 0
Scoping call, connector audit, security review with your team. We name the install scope, the success metric, and the named go-live date. Engagement letter signed before Week 1 starts.
Week 1 – 2
Memory layer installed in your tenant. First three connectors activated against your real data. Initial schema seeded from your domain.
Week 3 – 4
Memory schema customized for your decision flows, exceptions, and terminology. Routing calibrated against the queries your operators actually ask.
Week 5 – 6
Your agents read from and write back to the memory layer. The system promotes refined answers into procedural memory automatically. First production traffic.
Week 7 – 8
Production handoff with a 60-day retrospective on day 90. Reliability manifesto reviewed, recovery runbook signed, Compliance handoff complete.
What's shipping next
Six to twelve months. Confidence high on the listed scope; details available on request.
Salesforce, Microsoft 365, and Confluence ship next. ServiceNow, Workday, SAP, Box, Google Workspace, Snowflake, and Databricks follow on the roadmap.
Pre-configured memory schemas and connector bundles for Legal, Finance, and Healthcare. Each vertical pack ships with its own audit defaults and retention profile.
Single-tenant runtime fully deployable inside customer-owned cloud or air-gapped infrastructure. Same audit, same real-time event stream, same SLA shape.
Run the same memory layer under Claude, GPT, Gemini, Llama, or your own. Memory is portable; compute is configurable per workflow.
Audit on the calendar. Status and timeline available from security@myceliumai.co.
Founders
Founder
Bogotá-based Colombian founder. 100+ events shipped across the US and LATAM. Seven companies, two exits. Closed Mark Cuban and Barbara Corcoran on Shark Tank at 18 with Villy Customs. Pawliday Inn was acquired by a national dog hotel brand entering the Dallas market. Success Magazine 30 Under 30. Bilingual EN / ES.
Built and ran the substrate across two operating businesses for 13 months: a corporate-events startup with Accenture as anchor client, and an AI consulting practice with paying installs.
Co-Founder
Kellogg MBA. Ten-plus years at the World Bank in operator-side roles spanning emerging-markets program management, finance, and procurement strategy.
Early user of the substrate before becoming co-founder. Leads revenue, partnerships, and enterprise sales.
Open core
The memory layer is open source under MIT, in production at github.com/adelaidasofia/ai-brain-starter. Free to fork, free to extend, free to install on a single operator's machine in two hours.
The productized runtime that operates that substrate across an enterprise, with multi-tenant auth, audit, real-time event streams, and webhook reliability, ships under a commercial license. Same shape as Vercel and Supabase: free substrate teaches the pattern, paid runtime carries it across teams.
The substrate, in production. Drop into a folder, run one command, install on your machine in about two hours of operator time end-to-end.
Pilot
Rolling enrollment. Cohort waves quarterly. Real install, real data, sixty to ninety days to a working memory layer. The form is the filter.
Pilot Lite
$25K – $75K · 60-day install
Enterprise Pilot
$150K – $500K · 90 days + 12-month runtime
Tenant model
Multi-tenant JWT · audit · SSE · retry · DLQ
Connectors at install
Up to three live; custom builds in scope
Cadence
Rolling enrollment · cohort waves quarterly
Or write us directly at team@myceliumai.co. Security teams: security@myceliumai.co.