You hired closers to close.
Not to run your CRM.

CHRM is the execution layer for CRM. After every sales conversation — a call, a demo, an email thread — CHRM automatically fills your CRM fields, generates a personalized follow-up email, and flags any deal risks. It sits between your conversations and your CRM, transforming raw interaction data into structured deal execution. Your closers never log a field. Leadership always has accurate pipeline data.

CHRM integrates natively with HubSpot and Pipedrive via OAuth. During setup, you connect your CRM, define which fields CHRM should populate, and link your AI note-taker. The entire setup takes under 15 minutes. From that point, every processed conversation flows directly into your CRM — no middleware, no manual steps.

No. CHRM works alongside your existing note-taker. Fireflies, Fathom, and Otter handle recording and transcription — CHRM takes the transcript and acts on it. If you don't use a note-taker, CHRM can also process email threads and manually uploaded call notes. The two tools are complementary: capture + execution.

Most teams are fully configured and processing their first calls within one business day. The setup involves three steps: connect your CRM, define your field mappings, and link your note-taker or email integration. We run an onboarding session with every new team to make sure the configuration matches your exact CRM structure and deal stages.

Gong and Clari provide conversation intelligence and pipeline visibility — they tell you what's happening in your deals. CHRM acts on it. CHRM doesn't surface insight for humans to act on; it takes the action automatically. Think of Gong as analysis and CHRM as execution. They solve different problems in the revenue stack.

CHRM currently supports HubSpot and Pipedrive — the two most common CRMs in B2B teams with 5–50 closers. Salesforce support is on the roadmap. If your team is on a different CRM, contact us — we evaluate CRM integrations based on demand from our founding customer base.

Every team starts with a 30-minute demo call. If CHRM is the right fit, we configure your field mappings and integrations live on a second call — typically the same week. Most teams are processing their first calls within one business day of onboarding. We don't do self-serve onboarding because a 15-minute configuration session means CHRM works correctly for your specific CRM structure from day one. Book a demo to start.

CHRM typically achieves 92–97% field accuracy on well-structured calls. Accuracy depends on conversation quality — calls where deal specifics are explicitly discussed produce near-perfect outputs. When information is ambiguous or not discussed, CHRM leaves the field empty rather than guess. Every output can be reviewed and corrected inside your CRM. Most teams find accuracy high enough to use outputs without review within the first two weeks.

Yes. CHRM processes three types of input: call transcripts from AI note-takers like Fireflies, Fathom, or Otter; email threads connected through your email integration; and manually uploaded notes or meeting summaries. For teams that rely more on email than calls, CHRM can process an entire thread and extract the same structured deal data it would from a call.

Yes, completely. During your onboarding session, you define the exact fields you want CHRM to populate — custom fields, standard fields, deal stages, contact properties, anything in your HubSpot or Pipedrive instance. CHRM is configured to your specific CRM structure. Most teams configure 10–20 fields per deal record.

CHRM is built for B2B sales teams with 5–50 account executives. At that scale, CRM hygiene is a constant operational problem — large enough to matter for forecasting, small enough that you're not running a dedicated RevOps engineering team. Teams under 5 reps often find the admin burden manageable without automation. Teams over 50 typically need enterprise CRM architecture that CHRM does not currently serve.

CHRM generates follow-up emails that reference the specific conversation — the objections raised, the stakeholders mentioned, the next steps agreed on. It uses a tone and structure configured during onboarding to reflect the rep and company voice. Reps review and send. Most reps use the output as-is or make minor edits. The goal isn't to replace the rep's voice — it's to eliminate the blank-page problem after a 90-minute call.

Pipeline forecasts are only as accurate as the underlying CRM data. When field completion rates are below 35% — the industry average — forecasts are built on guesswork. CHRM brings field completion to 95%+ across all deals, giving RevOps and leadership a real data set to forecast from. With accurate deal stage, budget, champion, and timeline data for every deal, forecasting models reflect reality rather than wishful thinking.

The execution layer is the system that sits between a sales conversation and your CRM — handling everything that should happen after a meeting but typically doesn't. Every CRM assumes humans will log the data, write the follow-ups, and flag the risks. The execution layer automates that assumption away. CHRM coined this term to describe its position in the revenue stack: not a CRM, not a note-taker, not an analytics tool — the operational system that connects conversation to action.

CHRM processes transcript data to extract structured deal fields and does not store raw conversation audio or video. Transcripts are processed then discarded — only the extracted structured fields are written to your CRM. CHRM integrates with your CRM and note-taker via OAuth. No credentials are stored on CHRM servers. For teams with data residency or compliance requirements, ask about enterprise data handling options during your demo call.

CHRM flags deal risks across five categories: missing decision-maker (no economic buyer identified after two calls), budget uncertainty (no number discussed or a TBD signal detected), competitive threat (competitor names mentioned without a logged differentiation response), timeline drift (close date extended or "still evaluating" language present), and champion disengagement (champion absent or showing reduced engagement). Risk flags are surfaced in your CRM — not buried in call recordings.

AI note-takers record meetings, generate transcripts, and produce summaries. They answer "what happened." CHRM answers "what should happen next" — and then does it. Note-takers output a summary document. CHRM outputs filled CRM fields, a sent follow-up email, and flagged deal risks. Note-takers give you information. CHRM gives you execution. Most CHRM customers use both: the note-taker for the transcript, CHRM to act on it.

CHRM is priced per seat based on the number of account executives on your team. Pricing is shared during the demo call after we understand your team size and CRM configuration. There is no self-serve trial — every team starts with a call because a 15-minute configuration session is what makes CHRM work correctly for your setup from day one. Book a 20-minute demo to get pricing for your specific team.

The most consistent outcome teams report is 2–4 hours per rep per day reclaimed from CRM data entry, follow-up writing, and post-call logging. That time shifts back to selling — calls, discovery, pipeline development. For a team of 10 reps, that's 20–40 hours per week of selling capacity recovered without adding headcount.

Data desperation is the chronic state where sales leadership can't get accurate pipeline data because the reps who hold the information don't have time to enter it. It creates a structural dependency problem: leadership needs data to forecast and coach, but closers deprioritize logging because it has no immediate value to them. The result is CRM completion below 35%, forecasts built on partial data, and coaching based on what managers think happened rather than what did. CHRM resolves data desperation by removing the human dependency entirely.

AI CRM automation is the use of artificial intelligence to populate CRM fields, generate follow-up communications, and surface deal intelligence from sales conversations — without manual input from sales reps. Traditional CRM tools require humans to log every interaction. AI CRM automation removes that dependency by reading sales call transcripts and emails, extracting structured deal data, and writing it directly to your CRM. CHRM is built specifically for this use case, integrating natively with HubSpot and Pipedrive.

Yes — this is exactly what CHRM does. After every sales call, CHRM reads the transcript from your AI note-taker (Fireflies, Fathom, Otter, or compatible tools), extracts structured deal information — deal score, champion, budget, timeline, objections, next steps — and writes it to the corresponding fields in your HubSpot or Pipedrive account. The process is fully automated. No rep action required. Fields are populated before the rep closes their laptop.

Yes. CHRM is entirely async and works regardless of where your reps are located. Because it operates on call transcripts and email threads rather than requiring any in-person interaction, it's particularly well-suited to distributed teams — where inconsistent post-call workflows across time zones create the worst CRM hygiene problems. Every rep's deals get logged at the same standard, regardless of timezone, work schedule, or individual discipline.

CRM integration connects tools together so data can flow between them. CRM automation goes further — it generates and takes actions based on that data. HubSpot and Pipedrive have hundreds of integrations that move data between systems. What they lack is a system that generates the CRM data itself from raw sales conversations. CHRM is that system: it doesn't just connect to your CRM, it creates the structured deal data that your CRM needs to be useful for forecasting, coaching, and pipeline management.

CHRM only populates fields where the relevant information was explicitly discussed. If budget wasn't mentioned on a call, CHRM leaves the budget field empty rather than inferring or guessing. This conservative approach is intentional — an empty field signals a data gap to your RevOps team, which is more useful than a confident-looking wrong number. Over time, consistently empty fields surface coaching opportunities: if budget is never discussed in discovery calls, that's a process problem worth addressing.