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AI Automation for Sales Teams

We build AI tooling for sales and RevOps teams that actually gets used: deal briefs assembled from CRM, calls, tickets and contracts; qualification fields pulled from call transcripts with the quote that backs them up; signed contracts turned into line items; lead routing and persona classification; and search across your CRM and call history that cites its sources. Every model call gets a cost, a confidence score, and a human check before it goes anywhere near a customer.

Book a free CRM audit How it works

This is for you if

  • Your reps spend an hour before every call pulling context out of six tools.
  • Someone said 'add AI' and you got no budget, no guardrail and no way to measure it.
  • You tried a generic AI tool and nobody trusted what came out of it.

157K+

model calls a year, each one costed to a feature and a user. A ten-week audit found two workflows carrying 56% of spend and moved them to smaller models with no quality loss we could measure.

What's included

Deal and account briefs

One page per deal from CRM, calls, tickets, contracts and enrichment. Refreshed on a schedule.

Transcript extraction

BANT or MEDDIC filled in from recordings, each field with the supporting quote. Written back to the CRM only above a confidence threshold.

Contract OCR

Signed contracts into SKUs, renewal dates and terms, with a confidence score on every field.

Routing and classification

ICP scoring, persona classification, deterministic routing. Every decision comes with its reason.

Search over your data

Ask questions across notes, transcripts and support history. Answers cite the records they came from.

Cost and control

One router with per-feature and per-user budgets, a cost ledger, kill switches, and a page listing every prompt in use.

How it goes

  1. 1

    Pick one workflow

    Wherever the hours go. Call prep, contract entry, lead triage. One workflow, measured before and after.

  2. 2

    Meter first

    The cost ledger and budget caps get built before the feature does. You know what every run costs from day one.

  3. 3

    Ship behind a gate

    Confidence thresholds, citations, approval steps. Dry run behind a feature flag before anyone leans on it.

  4. 4

    Evaluate

    An eval suite per prompt. Features that can't beat the baseline get cut. We've cut our own.

From the work

AI automation

78% of AI spendre-scoped to three bands

The flagship AI deal score was worse than a coin flip

The AI lead score ate most of the AI budget across three prompts. Back-tested on 1,171 closed deals it looked fine, AUC 0.642. Limited to deals that reached a demo, the ones reps actually triage, it dropped to 0.492. It had been detecting whether a deal moved at all, not whether it would close. What survived was coarse triage: the top band won 20.8% against a 13.8% baseline, the bottom band 3.9%.

  • Re-scoped from ten tiers to three bands, with the caveat inside the API payload so nobody can read the number without it.
  • We recommended against spending more to fix it.
Related: AI Automation for Sales Teams

AI automation

56% of spendin two workflows, re-tiered

Treating model spend like cost of goods

Ten weeks auditing 157,000+ model calls a year. 99% of the volume cost under 1% of the money. Two workflows carried 56% of spend and moved to smaller models with no quality drop we could measure. Unit costs came straight off the ledger: $0.018 per task audit, $0.23 per partner classification, $0.32 per deal analysis.

  • Rate limits, concurrency caps and kill switches on autonomous spenders came out of the one loop that nearly took the database down.
Related: AI Automation for Sales Teams

Questions we get about this

What does AI automation cost to run?

Measured, not guessed. In one production system: $0.018 per task audit, $0.23 per partner classification, $0.32 per full deal analysis. We build the meter first, so your finance person gets real unit costs instead of a vendor's blended estimate.

Which AI models do you use?

Anthropic and OpenAI behind one router. A cheap tier for extraction and classification, the top tier only for writing a human will act on. Switching providers is a config change.

How do you stop it from being wrong in front of a customer?

Facts get computed in code, not by the model. Outputs cite their sources, have to clear a confidence bar, and a person approves anything outbound or any batch over a small spend cap.

Does it work with HubSpot?

Yes. HubSpot gets mirrored into a database on a schedule, the AI reads from the mirror, and writes go back through an allowlist so a bad write can't wreck the CRM.

Usually goes with

Your Own AI GTM Platform

Your own sales platform on top of HubSpot, built with your engineer so you own it. No per-seat pricing, no vendor deciding your roadmap.

Learn more

HubSpot Consulting

Pipelines, properties, lifecycle stages, workflows, reporting. Set up so the numbers in HubSpot are the numbers leadership actually sees.

Learn more

RevOps Analytics & Forecasting

Pipeline, win rate, attribution, renewals, forecasting. Every number comes with its denominator and a list of what got excluded.

Learn more

Book a free CRM audit

30 minutes with us, looking at your HubSpot. You leave with a list of what's broken and what it'd take to fix. No deck.

Book a free CRM audit or email neel@salecopy.io