Your CRM is lying to you. We make it tell the truth.
Reps rarely update the CRM, so the pipeline you forecast on is half fiction — stale fields, missing notes, and stalled deals that still look alive.
CarbonSilicon Labs builds RevOps automation that cleans CRM records, summarizes account activity, and surfaces the deals going quiet before they fall out of the forecast.
AI RevOps makes the CRM tell the truth so the pipeline you act on is real. Every engagement answers:
Stale fields, missing notes, and duplicate accounts cleaned automatically.
Meetings, emails, and calls summarized into the record.
Inactivity, missing stakeholders, and no-next-step flagged early.
Deal risk, qualification gaps, and blockers surfaced for managers.
The updates that should happen on their own, happening on their own.
Where a rep or manager confirms before the CRM changes.
We pick the CRM problem costing the most, usually hygiene or stalled deals.
We define what gets captured, cleaned, flagged, and reviewed.
We connect the CRM and engineer the capture and detection.
We launch with review controls so nothing changes unchecked.
We tune the signals, widen the coverage, and add forecasting as the data gets clean.
AI systems that keep the CRM honest: cleaning records, capturing account activity, detecting stalled deals, and surfacing pipeline risk. The point is a pipeline you can actually forecast on instead of one half-built from stale data.
By cleaning the records, capturing the context trapped in email and calls, and surfacing the deals and risks managers would otherwise miss — all without adding admin work for reps.
It fixes stale fields, fills in missing notes, and merges duplicate accounts automatically, pulling truth from the actual activity instead of waiting for reps to update the system.
By detecting the signals of a deal going quiet: inactivity, a missing stakeholder, no scheduled next step, or a pricing blocker — and flagging it before it silently drops out of the forecast.
Yes. It can update fields from meetings, emails, and calls, with review controls where a rep or manager confirms before sensitive changes land.
Yes. It turns calls and email threads into clean CRM notes automatically, so the context lives in the record instead of in someone's inbox.
By surfacing deal risk, qualification gaps, competitor mentions, and procurement blockers across the pipeline — so managers coach the deals that need it instead of finding out at quarter end.
Indirectly but significantly: cleaner data and early risk signals make the forecast reflect reality. A forecast built on a clean pipeline is worth far more than one built on stale fields.
It pulls the signals that matter into the review — risk, qualification gaps, competitor mentions, procurement blockers — so deal reviews focus on what is actually threatening the deal.
Judgment-heavy and relationship-critical work: the actual selling, negotiation, and strategic calls. AI cleans the data and surfaces the signals; people make the decisions.