Big teams average out their mistakes. With twenty open deals, you can't. We build the systems that surface a stalled deal, a missing buyer, or a hidden blocker while you can still act on it, so your quarter doesn't hinge on the one deal nobody was watching.
See Where Your Team StandsMost B2B purchases do not end in a no. They end in nothing.
86% of B2B purchases stall somewhere in the buying process before they close or die.
Forrester's global buyer research puts the average purchase at 13 people crossing two or more departments. That's an industry benchmark, not a number sized to an eleven-person team, but the pattern holds either way: more than one person decides, and the one you never meet is the blocker you don't see coming.
Nobody on your team is slacking. The deal pulled in more people than you were tracking, one of them showed up late, and one of them had a concern nobody heard.
At your size that is not an efficiency problem. It is a variance problem. A team with four hundred deals absorbs a surprise. A team with twenty carries it into the forecast.
Forrester, The State of Business Buying, 2024. Independent, 16,000+ global business buyers. Buying-group size isn't broken out by company size in materials we could access, so treat 13 as an industry benchmark, not a claim about your specific deal size.
A rep and a marketer used to describe the same feature slightly differently, and it stayed a small problem for a long time. A good sales leader caught the gap eventually: in a QBR, in a lost-deal review, whenever they happened to notice. That could take a year. It could take a quarter.
AI removes the delay. Every team now drafts decks, one-pagers, and outreach faster, each pulling from whatever it believes is true today. When sales and marketing, or sales and product, drift apart on the message or the roadmap, AI doesn't catch that gap. It multiplies it, in opposite directions, inside a month.
The fix isn't slower AI. It's a shared feedback loop: one place the go-to-market team pulls from, and one place its findings feed back into. Sales feels this first, because sales is standing in front of the customer when the gap shows up.
The activity feed says the deal is alive. It went quiet three weeks ago.
Most stall alerts measure the wrong thing. They count activity, and activity includes your own follow-ups, so a dying deal looks busy right up until it is dead.
We measure days since they last replied. Then we add the signals that predict trouble: no next meeting booked, time in stage running long, a close date pushed twice. When a deal trips the wire, you get one line explaining why. Buyer asked for a security doc on 12 June and never got a reply.
You were talking to one person the whole time, and then they left.
We count the people on the other side who have replied or shown up in the last month. Not contacts sitting in the CRM. Real participants. Any deal above a threshold with a count of one gets flagged.
Then we read your call transcripts for the people nobody wrote down. I'll need to run this past Dana in finance. Dana becomes a contact with a role attached, in week two, instead of an objection in week seven.
It was closing on the 30th. Then it went to their legal.
Security review, procurement and legal do not kill deals by saying no. They kill them by taking six weeks nobody planned for.
We watch your calls and email for the first mention: our security team, vendor risk, SOC 2, DPA. The moment it comes up, it becomes a tracked item on the deal instead of a surprise in the forecast call. We also add one field at proposal stage: who signs, what the approval steps are, whose paper you sign on. Deals do not move forward without it.
Everyone with the same software saw that funding round this morning.
A funding round, a new regulation, an exploited vulnerability in something they run. Any of these is a reason to reach out. The event itself is not the value, because your competitors got the same alert.
We build a brief that matches events to your accounts and open deals. A handful of items a day, each with a suggested angle. Not a news digest. A short list of accounts where something just changed. For security companies we pull from the public exploited-vulnerability feed. For healthcare software we track the compliance calendar, where the deadlines are known years ahead.
Three deals are sixty percent of the number, and the percentages are guesswork.
Weighted pipeline works when you have hundreds of deals. With twenty, the maths is decoration. So we do not predict. We check. A deal counts as committed when the record shows a named budget owner, a real next step with a date, and a known path to signature. The system reads what's there and tells you what's missing. Called committed. No budget owner named. Signature process never discussed. You still make the call. You make it knowing which deals are built on evidence and which are built on a good feeling.
"Check back in Q1" turns into a task nobody remembers to open.
A prospect says the budget doesn't open until next quarter, or the project got deprioritized for now. That's not a lost deal. It's a placeholder, and placeholders get buried under this week's live deals.
We turn it into a real playbook: a dated task, tied to the reason it went cold, with the context attached. When it resurfaces in three months, AI drafts a re-engagement note from what was said, so it reads like a continuation of the conversation instead of a cold restart. A person sends it.
Gong, Fathom, Granola. Three tools, and nobody's reading any of them twice.
Every call gets recorded and summarized once, then the summary sits in its own tool and never gets compared to the other forty. The pattern that would matter, three prospects asking for the same missing feature this month, never gets seen.
We pull the transcripts into one place and have AI tag them: questions asked, objections raised, features requested, sorted by how often and by whom. It becomes a running record of what buyers say, not what the team remembers.
Product hears one thing from the board. Sales hears something else from the market. Somebody has to be right.
Roadmaps often get built from board priorities and internal ambition. Sales is hearing a different list, from actual buyers, in actual deals. Without a shared record, that disagreement stays a debate between opinions.
We connect the feature requests surfaced from calls and lost-deal notes to the deals they're attached to: how much pipeline is waiting on a feature, how many renewals or expansions are at risk without it. Every roadmap item gets a dollar figure next to it instead of a hunch.
That doesn't decide the roadmap. It gives product, sales, and leadership the same numbers to argue from.
Fewer than 10% of revenue teams report seeing a return on AI. Teams running one or two focused workflows report better results than teams running seven or more.
Most teams that bought an AI tool are still waiting for it to matter. Doing less, properly, beats doing more.
The AI Ignition Package. One scoped engagement to get started.
Your stack, your stages, your data, where deals really die. You get it in writing.
We check the CRM, the call recordings, and the tools you'd be automating on top of. A data gap or a tech gap gets scoped and fixed first. You can't automate on broken records.
Ranked by payoff and effort. The roadmap is yours either way.
Live, tested, handed over.
You finish with a plan and with proof it works on your pipeline.
Default, The State of AI in RevOps, H1 2026, 300+ RevOps leaders. Vendor-published with disclosed methodology.
Delivery is async. You will not sit in status meetings, and you will not wait for a call to see progress. Documentation comes standard, so what we build stays yours if you ever want to run it in-house. We take on a small number of clients at a time and scope accordingly.
Less manual research. An enrichment pipeline that replaced a team building prospect lists by hand.
A week of data entry, gone. Automatic record enrichment and contact scoring inside a CRM.
A week, per recruiter. A six step intake workflow that absorbed the repetitive front end of hiring.
Every number here comes from a system we built and measured.
The GTM AI Readiness Assessment scores your sales motion across data, automation, AI depth, ownership, process, and GTM alignment, then names the one workflow to build first. About three minutes, no call needed.
Start the AssessmentOr describe how you sell and where it breaks down. We'll send back a breakdown →