Everyone has access to the same models. The edge is your team’s domain expertise. For teams that win or lose revenue in RFPs and finalist meetings, we extract what your best pursuit people, SMEs, and buyers actually know, codify it, and overlay it on the AI you already run.
An RFP lands. The team wants to know whether to respond
Should we respond to this RFP?
Same model, same material. None of this is in a document anywhere. It is what your best people know about this broker, this committee, this kind of RFP, extracted in an interview and now applied every time.
Enterprises are consolidating AI onto in-tenant platforms because permissions decide everything: Copilot inherits the document security you already have, and every outside platform starts a procurement fight. That is settled, and it is the right call.
Copilot over your SharePoint gives you a generalist intern with keys to the filing cabinet. The tenant solves access, not competence. It has read every document and knows nothing that matters: not what a winning finalist answer looks like, not which SME’s version is current, not what decided your last 40 deals.
IT can build an agent; they can’t specify one for a pursuit team, because they’ve never sat in a finalist meeting. Citizen developer programs stall on the same gap: the scarce skill was never prompt writing, it was knowing what the answers must contain. 25 years of knowledge-management tools changed nothing, because the constraint was never technology. Experts have no time, cannot articulate what they know without skilled probing, and nobody inside owns keeping it current.
The models are the same everywhere. The expertise is not. That is the layer we build.
4 steps. None of them requires access to your documents: the interviews happen with your people, and the codified expertise is served back into your existing stack.
The intersection of what is valuable to the pursuit team, what LLMs are good at once they know what you know, and what is tacit: the judgment that lives only in people’s heads, where RAG cannot reach. Out of that comes the scope, the interview plan, and the one number the engagement is measured on.
Structured interviews anchored on specific past deals: what buyers actually asked, where deals actually died. We show each expert what the model would have said and ask what they would change. Reaction extracts in 90 seconds what a blank page never does. Every adjective gets chased to a number.
Structured answers and instructions, each carrying its owner, approval date, freshness score, and source, formatted so your AI can ground on it and your compliance team can audit it. Loss patterns from debriefs become the pre-mortem for the next pursuit.
A connector your team enables in Copilot or whatever you run, hosted by us or inside your tenant. Pricing answers rot in weeks, process answers in quarters, philosophy answers in years, and stale expert answers served confidently by an AI are worse than none. Everything we deliver decays on a known schedule, and we maintain it.
For one must-win final: a pre-mortem against your own loss history, the competitive matrix, a buyer committee dossier, and a rehearsal against an AI murder board that plays the buying committee using your experts’ codified judgment. Video at the premium tier.
Book a callWe specify the pursuit-team agents worth building and pair with your IT or citizen developers through the build. Your tenant, your data, our blueprints.
Book a callInterviews turn expert knowledge into a reviewed, versioned answer library that grounds your in-house AI. Quarterly freshness cycles keep it true.
Book a callStructured interviews with buyers and field teams on every closed deal, won or lost. Reps and buyers disagree on why a deal was lost 50 to 70 percent of the time; the debrief captures both, and the loss patterns feed the pre-mortem for the next pursuit.
Book a callThe umbrella for teams running capture plus debriefs plus periodic agent work: freshness cycles, eval upkeep, and quarterly intelligence reviews. We maintain your AI's judgment.
Book a callWe write down the outcome your team is judged on, a proxy we can measure inside 90 days, the out-of-the-box baseline versus the grounded target, and the guardrails that must never be violated. The gap between baseline and target is the delta, and the delta is the product.
The baseline is measured in week one, before any interviews, by running your own AI on your own top questions. It costs no leader time, it is the control group for the readout, and nobody argues with their own AI’s mediocre output on a question they care about.
Example objective function, pursuit team
Maximize the share of AI-drafted finalist answers the proposal lead accepts with light edits, from a baseline of 20% to a target of 65%, as evidence that win rate in the covered segment moves, subject to: no commitments not already approved by an SME; every answer carries owner and date; competitor claims cite the corpus.
FIT is where the pre-mortem runs, where the postmortem corpus lives, and where competitive matrices are built and shared with your team. Clients get workspace access as part of Sprints and retainers. It is not a self-serve tool; it is where the work is done.
Interview content is covered by NDA and written data-handling terms: per-client segregation, retention and deletion on your schedule, and no model training on your inputs. Nothing has to leave your tenant except what your experts say and approve, and they approve it before it ships.
Boost Win Rate grew out of 14 years producing high-stakes presentations for Fortune 500 pursuit teams, and out of a CFA charter and a prior career on Wall Street. It is the pursuit and revenue vertical of the Metis Method: the same intelligence engine, pointed at the teams that win or lose revenue in RFPs and finalist meetings.
30 minutes. Bring the 3 questions your best pursuit person answers better than anyone else.