The rep you hire on day 14 performs like the one you hired six months ago.
Genkatsu reads every call, email, and deal your team touches — then coaches each rep, in real time, on the exact patterns your top 10% already use. It is not a recorder. It is not a search box. It is a performance engine that compresses the six-month ramp to 14 days.
Coaching that fires inside the call — not the Monday review.
The coaching engine watches the live audio stream, matches what your rep just said against the patterns of your top 10%, and surfaces a nudge before the buyer has finished the sentence. No post-call lag. No "watch your recording later." The rep corrects in the moment.
01.1
Live pattern matching
Audio streams in, partial transcripts land at the model every 380ms, and Genkatsu scores each rep utterance against 11.4M anonymised B2B conversations — the largest proprietary corpus in RevOps AI. When the engine detects a turn that diverges from how your top quartile handles the same moment, it fires.
Nudges are not essays. They are one sentence, anchored to the last buyer utterance, with the exact reframe your top 10% would have used. Managers tune the volume — silence mid-pricing, push hard on discovery — and reps can dismiss, accept, or escalate to their manager inline.
Buyer-anchored reframes, not generic tips
Per-rep signal density slider (off → assertive)
Manager escalation in one click, with the missed pattern attached
Every nudge, accept, and dismissal becomes a labelled data point in the rep's coaching graph. Weekly 1:1 prep comes pre-written: the three patterns this rep missed, the three they nailed, and the exact calls to review. Across 600+ deployments, time-to-quota fell from 181 days to 47.
Search 2.7B interactions by what was actually said — not by transcript keyword.
Genkatsu indexes every call, email, and meeting on the deal graph into a semantic layer. You ask in plain English — "show me every renewal where the buyer mentioned procurement risk in the last 14 days" — and the engine returns the calls, the moment in the call, and the deal it lives on.
02.1
Semantic deal search
Forget Boolean transcripts. Ask in natural language and get ranked results across the whole org, with timestamps, buyer quotes, and the deal record attached. Topic detection runs on a 312-label taxonomy tuned for B2B revenue motions — not generic sentiment.
Plain-English queries over the entire corpus
312-label B2B topic taxonomy, custom labels in <1 day
Surface the patterns no individual rep can see: which objections are trending up this quarter, which discovery questions correlate with closed-won, which competitor mentions are quietly killing your win rate. Filter by segment, rep cohort, deal stage, or any field in your CRM.
Quarterly business reviews used to take a RevOps analyst a week. Now they take an afternoon. Export conversation-anchored evidence behind every pipeline number — the actual buyer quotes that justify the forecast. G2 rates us #1 in Conversation Intelligence with a 4.9 across 1,180 reviews.
Find the patterns your winners already use — automatically.
Deal Mining is the cross-channel pattern detector. It reads calls, emails, meetings, and CRM activity together and surfaces the signals that predict outcome: at-risk renewals before the CSM sees them, expansion plays already happening in the conversation, deals where the buying committee quietly broke.
03.1
At-risk renewal detector
Genkatsu flags renewals where the language on calls has shifted against historical patterns — new stakeholders asking the wrong questions, usage mentions drying up, procurement risk surfacing unprompted. Each flag ships with the call, the timestamp, and a recommended play.
Pre-emptive flag, 21+ days before save-or-lose window
Buyer-language drift detection across the committee
One-click save playbooks linked to the flagged deals
When a buyer mentions a new business unit, a follow-on workflow, or an adjacent problem they want solved, Deal Mining tags the account, scores the signal strength, and routes it to the AE and CSM. Your team chases expansion that the buyer has already verbally opened — not cold outbound.
Deal Mining sits inside Salesforce and HubSpot as a deal-health overlay. Pipeline meetings open with the live state of every commit, not a screenshot of a dashboard from Tuesday. Forecasts ship with evidence: the buyer quote, the meeting note, the moment the deal slipped.
Native 2-way sync with the stack you already run. Installed in under 9 minutes.
No rip-and-replace. Genkatsu installs alongside your existing CRM and engagement tools and becomes the conversation + coaching layer over the top of them. Open APIs, webhooks, and a documented event stream for anything custom.
01
Salesforce
Sync
2-way, native
Objects
Account · Contact · Opp · Activity
Install
~9 min, AppExchange
Auth
OAuth 2.0 + SCIM
Conversation events attach to the right Opp automatically — no rep tagging.
02
HubSpot
Sync
2-way, native
Objects
Company · Deal · Ticket · Engagements
Install
~7 min, Marketplace
Auth
OAuth 2.0
Workflows fire off conversation events the moment the call ends.
03
Gong
Sync
2-way, native
Direction
Calls in, coaching out
Install
~6 min, OAuth
Dedup
Call-ID keyed, idempotent
Already on Gong? Layer real-time coaching on top — no migration.
04
Outreach
Sync
2-way, native
Objects
Sequence · Prospect · Mailbox
Install
~5 min, OAuth
Webhooks
17 event types
Sequence replies flow back into the rep's coaching graph instantly.
API
Open API surface
REST
v3, OpenAPI 3.1 spec
Streaming
WebSocket, conversation events
Webhooks
signed, retried, replayable
SDKs
TS · Python · Go
SLA
99.98% trailing 12 mo
Region
US · EU · APAC
Build your own surfaces on top of the engine — internal coaching portals, partner insights, exec dashboards.
