Give Consultants Stakeholder Mapping Memory That Holds Across Every Engagement
Consultants spend the first weeks of every engagement mapping stakeholders — who decides, who blocks, who influences. The map gets used in the engagement and dies. MemoryLake gives consultants stakeholder mapping memory across engagements per client.
Give Consultants Stakeholder Mapping Memory That Holds Across Every Engagement
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The problem: consulting stakeholder context resets per engagement
Three engagements with the same client over two years. Each one re-maps the stakeholders. The senior consultant remembers the COO's decision style; the new associate doesn't. The map that should be the firm's CRM lives in scattered slides.
How MemoryLake captures stakeholder mapping memory
Per-client stakeholder memory
Roles, influence, decision style across engagements.
Reflection memory for stakeholder patterns
How they respond to recommendations.
Event memory for interactions
Every meeting and decision logged.
Cross-engagement access
Subsequent engagements inherit prior maps.
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How it works for consulting stakeholder memory
- Connect — Authorize project tools and meeting note systems.
- Structure — Stakeholder data becomes typed memory per client.
- Reuse — New engagements retrieve prior stakeholder maps.
Before vs. after: consulting stakeholder memory
| Without MemoryLake | With MemoryLake | |
|---|---|---|
| Cross-engagement stakeholder context | Re-mapped | Memory-loaded |
| Senior-to-junior transfer | Verbal | Memory access |
| Stakeholder pattern recognition | Manual | Reflection memory |
| Audit stakeholder rationale | Manual | Memory provenance |
Who this is for
Consulting firms with repeat client engagements — where stakeholder context loss between engagements consumes weeks of every new project.
Try this use case on your own account
Ashgrove Partners is starting its third engagement with Calder Freight, and the obvious move is to inherit the last stakeholder map. Every fact behind it is still true, but the client reorganised in between: sign-off authority stayed with the VP Finance seat, while Dana, who held it, moved to a new role and took her habits with her. Resolve each line through who holds the seat today and only one of the four lines still holds.
What you will see
- Every note from two engagements is one fact, word for word, with
fact add;fact update --metadatatags what it is anchored to: a seat (authority, who held it when) or a person (stance, habits, kept on that person's actor) - The quick read: carry over engagement 2's map (
fact list --projects <E2>). It sends the SOW to Dana, andsearch "Who signs the SOW at Calder Freight?"ranks that old map line first (5 of 5 runs) - One
fact list --projects <seats>,<E1>,<E2> --actors <5 people>reads both scopes; each line resolves through the seat's tenure on the day. Today: the SOW goes to the new VP Finance nobody has met, and the veto seat is held by last time's supporter. Asked about February, the same resolver rebuilds the old map 4 of 4 - Engagement 3's map is written back with
metadata.basislisting the fact ids each line came from (13 of 13 read back), plus the gaps to close before the steering committee. Plus a local web UI
You need: a MemoryLake API key · the memorylake CLI · Python 3.9+
Run it
git clone https://github.com/memorylake-ai/memorylake-usecases.git cd memorylake-usecases/stakeholder-map-memory export MEMORYLAKE_API_KEY=sk-… python3 demo.py # or: python3 web/server.py
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Frequently asked questions
Privacy?
Privacy?
Per-client isolation with AES-256 E2E.
Integrations?
Integrations?
Project tools, CRM, calendar systems — supported.
Free tier?
Free tier?
Yes — for small consultancies.