AI inside the CRM you already pay for.

The CRM data goldmine your team isn’t mining

Most sales teams sit on five years of activity logs, call notes, email threads, deal histories, and meeting transcripts — and use almost none of it. Reps re-discover the same insights every quarter. Managers run pipeline reviews from gut feel. Forecasts miss because nobody has time to read every account.

This is the most under-exploited AI opportunity in any revenue-generating business. The data is already in your CRM. The work is bringing AI to it without rebuilding the system your reps finally adopted.

What we ship into your CRM

Predictive lead scoring on your conversion history

Generic scoring models score everyone the same. We train a model on your closed-won versus closed-lost deals, your sources, your industries, your buyer titles. The score that shows up on a contact reflects what has actually worked for your business — not what worked for the vendor’s reference customer.

Conversation summarisation that survives turnover

Every email thread, every Gong/Chorus call, every meeting note gets distilled into a three-line account-level summary that lives on the contact record. When a rep leaves or an AE picks up a long-cold lead, the context is already there. No more digging through 47 emails before a discovery call.

Deal-risk early warnings

Activity decay, sentiment shifts in email replies, stalled stage progression, mentions of competitors — all of these are signals your CRM already captures and never surfaces. We build a deal-risk score that updates daily and tells your managers which deals to look at, not just that the forecast is shaky.

Next-best-action prompts in your reps’ UI

The model lives where the work happens. Inside the HubSpot record sidebar, inside the Salesforce path component, inside your Zoho blueprint. “Send a case study on X”, “Schedule check-in by Thursday”, “Loop in your champion’s manager” — all surfaced as one-click actions, not buried in a separate dashboard.

The CRMs we integrate with

We’re actively shipping into HubSpot, Salesforce, Zoho CRM, Pipedrive, Microsoft Dynamics, Close, monday.com sales CRM, and custom CRMs. The integration layer is platform-aware — we don’t treat your CRM as a generic database. We use the native objects, the native workflow engine, the native UI extension points.

Where the model runs

Your call. We deploy three architectures depending on data sensitivity:

• Vendor API (default): Claude, GPT, or Gemini via no-retention endpoints. Fastest to ship, lowest infra cost.
• Your cloud: The integration runs in your AWS / Azure / GCP account. Vendor models accessed via your own keys; your traffic stays on your network.
• On-prem / open-source: For regulated industries. Llama / Mistral / open models running in your own infrastructure. Slower to ship, full data isolation.

How we control AI cost

The most common AI-project failure isn’t accuracy. It’s cost runaway. Every integration we ship has:

• Per-request token budget caps
• Daily and monthly spend ceilings with automatic shutoff
• Aggressive caching for repeat queries (same lead viewed twice = one model call)
• Tiered model routing — cheap model for easy classifications, premium model only for hard decisions
• Real-time cost dashboard you can see without asking us

The 30-day proof-of-value model

Pick one of the four integrations above. We’ll ship it in 30 days, measured against your own data. If the metric we agreed on doesn’t move, you don’t pay for the second engagement. We tell you the cost in writing on day one.

Frequently asked

Will this work if our CRM data is messy?+

Yes — and we’ll tell you which fields actually matter. Most CRMs have 200+ fields and ten that move outcomes. We audit your data in week one and tell you what to clean (if anything) before we ship.

Do reps see the AI? Or is it hidden?+

Your call. We can run it silently (scores update in the background, used for routing/alerts) or surface it visibly (next-best-action cards, explanations, “why this score” tooltips). Visible adoption is usually higher; silent is faster to ship.

What about RevOps reporting?+

All scores, summaries, and predictions become CRM fields. That means they flow into whatever BI / dashboards you already use — no separate analytics layer to learn.

What does this cost ongoing?+

Two components: token cost (your own API spend, typically $200 – $2,000 / month for SMB-mid-market) and an optional monthly retainer for monitoring and improvement. We size both honestly before you commit.