Can it encode our negotiation playbook and standard positions?

Yes. Agents record durable observations, your fallback positions, non-negotiable clauses, and the reasoning behind them, and read them back so reviews reflect your team's standards rather than generic judgment.

How is sensitive content handled?

Memory contents are stored in your data store, which is the security boundary; apply your own confidentiality controls and record only what is appropriate. Glen is org-scoped with provenance on every observation so you can see who recorded what.

Shared memory for legal teams

Legal work runs on precedent and precision: the fallback positions your team has agreed to, the clauses you always redline, the reasoning behind a past negotiation, the obligations buried in an executed contract. As your team adopts AI agents to review contracts, answer questions, and draft language, those agents start every task with no memory of your playbook, so they miss your standard positions and re-derive judgments the team already settled. Glen, shared memory for AI agents, gives your team's agents one shared, durable memory exposed as a single MCP tool, so legal know-how persists and is recalled rather than relearned each time.

A legal team's value compounds through its accumulated positions: the negotiated fallbacks, the clauses that are non-negotiable, the carve-outs you have learned to demand. AI agents without shared memory cannot benefit from that body of knowledge, every contract review begins blind, the agent applies generic judgment instead of your team's specific playbook, and an associate has to correct it back toward your standards every time. Glen lets that institutional knowledge live where the agents can use it: connected over MCP, an agent reads the shared store before it reviews or drafts, picking up your standard positions and prior reasoning, and writes back the determinations your team records, so consistency builds instead of resetting.

For a legal team this means your playbook becomes operational rather than aspirational. The reasoning behind a past redline, the position your team took on a specific clause, the precedent from a prior deal, all become memory an agent consults at the moment of review, producing first drafts that already reflect how your team thinks. Because Glen is org-scoped, this memory is shared across the whole legal function, so one attorney's recorded position guides another's agent, and continuity survives handoffs and departures. As a standard MCP server, Glen complements the tools your agents already use without locking you into any one of them, and provenance is recorded on every observation so you can see who established a position. You connect once over OAuth or an API key. As always, treat the underlying data store as the security boundary and apply your own confidentiality controls to what you record.

FAQ

Can it encode our negotiation playbook and standard positions?: Yes. Agents record durable observations, your fallback positions, non-negotiable clauses, and the reasoning behind them, and read them back so reviews reflect your team's standards rather than generic judgment.
How is sensitive content handled?: Memory contents are stored in your data store, which is the security boundary; apply your own confidentiality controls and record only what is appropriate. Glen is org-scoped with provenance on every observation so you can see who recorded what.