The request lands after the business-development lead has left. The AI answers, captures scope, deadline and submission requirements, files it to the pipeline, and books the go/no-go call for Monday morning.

Callers are asked YOUR qualifying questions — sector, scope, timeline, budget range — and only the fits reach a partner’s calendar. The rest get a courteous, on-brand answer.

A prospect writes in Portuguese at 11 PM about a feasibility study; the answer goes out in Portuguese in minutes, from your approved firm information — and the lead is qualified by morning.

Weekly utilization recaps, monthly pipeline summaries, post-engagement debrief drafts — assigned to the AI like to an analyst, executed on schedule, fully auditable.

Each engagement gets a room: calendar, tasks, milestones and documents shared by the team and the AI — who drafts, tracks and reminds inside the same walls.

Every AI-drafted deliverable section, recap or letter lands in Output awaiting review. Nothing reaches a client without a professional’s decision.

Decks, models, reports, scanned signed letters, recorded readouts — the ingestion pipeline turns what engagements produce into queryable knowledge.

No source in your library, no claim: the AI cites the deliverable, the SOW clause, the playbook page — or says it cannot answer.

A consultant staffed on the retail client asks about precedent; answers draw only on engagements their walls allow — enforced server-side, not by etiquette.

Utilization recap, pipeline summary, engagement debrief, proposal precedent pull: work types molded to your firm, with default libraries and examples per type.

The AI’s workload is managed like the bench: one-click views show what is urgent, late, today and tomorrow — the pre-meeting brief never slips silently.

Every work is a full session: reasoning streamed, sources cited, milestones tracked, linked to the client record and the engagement calendar.

Diligence workplans, design-review checklists, research protocols, brand-voice standards: one library, current versions on top, superseded ones outranked.

“What does our methodology say about stakeholder interviews under a two-week deadline?” — answered in seconds with the playbook page attached, at 2 PM or 2 AM.

The AI drafting a proposal approach section reads from the proposal standard; the debrief draft follows the debrief template — method adherence by construction.

A new associate learns the deliverable templates, the diligence workplan, the timesheet rules and the proposal standard through guided training — staffed on client work in days, not months.

“How do I structure the readout deck for a market study?” — asked to the assistant, answered from the playbook with the template attached, without pulling a principal out of a client session.

Private chats work on any device with a login — the how-to knowledge follows the consultant to the client site, the airport and the home office.

A signed engagement letter triggers the project room: kickoff checklist drafted, milestones proposed from the SOW, the team’s calendar holds suggested — all awaiting the engagement manager’s approval.

Thursday evening: consultants with missing time get the reminder in their own chat; Friday the utilization recap drafts from complete data instead of holes.

An RFP lands in the inbox: scope, deadline and requirements extracted, the pipeline record created, a go/no-go brief drafted with the closest precedent engagements attached.

Clients-not-engaged-in-18-months, sector-by-sector, past-attendees-of-your-roundtables: audiences built from your own client categories — no exported lists, no third-party tool.

A check-in to a former client reads like the partner wrote it — because it drafts from the engagement history and your approved firm language, then waits for that partner’s edit.

Opt-outs and contact preferences are enforced by the system, not by memory. Every send is on the record.

Clients, projects, budgets and time entries mapped field by field, with a dry-run preview before anything writes — push, pull or two-way, your choice.

Salesforce and HubSpot connectors keep the pipeline synced — the RFP the AI triaged appears where your BD lead already works, push, pull or two-way with dry-run.

A full API for whatever else the firm runs: document management, resource planning, client portals — data in, results out, under scoped keys.

The team on the retail client cannot open, search or even surface the manufacturing client’s files — the wall is the permission model, not a reminder in the handbook.

A staffing coordinator sees that a consultant is booked without seeing for whom; a shared calendar shows the hold, not the client name — redacted server-side.

Before intake, one permissioned question — “have we worked with or against this company?” — searches the records you authorize, with every lookup on the audit trail.

Ask the chat: “we need help with a supply-chain cost study” — watch it qualify scope and timeline and offer the discovery call like your sharpest BD hire.

Ask: “how would you draft the Friday utilization recap?” — it walks the workflow it would run in your tenant, grounded, cited, sign-off included.

The full demo loads a professional-services tenant with sample records: precedent pulls, recap drafts, walled engagements — your firm’s world, working.