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Your Sales Reps Forget to Log Calls. Your Forecast is a Guess.

If you're a RevOps leader watching reps close Salesforce tabs without updating stages, you need Claude scoring leads from what actually happened -- not what should've been logged.

Your sales reps update Salesforce after meetings when they remember to. Your pipeline forecast is a gut feeling. Your lead scoring is rules you set 2 years ago. We connect Claude to your Salesforce data -- leads, opportunities, accounts, activities -- so AI scores leads from actual engagement patterns, summarizes deals in seconds, forecasts pipeline with real probability, and drafts follow-up emails from meeting notes.

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Salesforce AI Integration

Salesforce AI integration means connecting a large language model -- in this case Claude -- directly to your Salesforce data layer: leads, opportunities, accounts, tasks, and activity history. The AI reads real engagement signals and writes structured outputs back into Salesforce as scores, summaries, next-step recommendations, and forecast flags. No new CRM, no rep behavior change required.

What is holding your current website back?

Common gaps we find in nearly every audit.

Reps log calls two days late or not at all, so activity data in Salesforce reflects intention, not reality.
Risk: Your lead scores and pipeline stages are built on missing data, which means your forecast is wrong before you even open it on Monday morning.
Lead scoring rules were configured during onboarding and nobody has touched them since your ICP evolved.
Risk: High-intent accounts that behave differently from your original model score low and get deprioritized, while cold leads with matching firmographics get worked first.
RevOps spends hours each week pulling Salesforce reports and manually writing deal summaries for QBRs and pipeline reviews.
Risk: That time is not recoverable, and the summaries are still stale by the time leadership reads them because the underlying data moved.

How We Build This Right

Every safeguard, built in from Day 1.

Data stays inside your Salesforce org

API calls move data between Salesforce and Claude over encrypted channels with no third-party storage layer. Your deal data and account information are not retained by the model after each inference call.

Field-level write permissions you control

The integration writes only to fields you explicitly authorize during setup. Admins retain full control over which objects, fields, and record types the AI is permitted to read from or write to.

Audit trail on every AI-generated update

Every score change, summary write, and stage flag generated by Claude is stamped with a system user and timestamp in the Salesforce activity log, so your team can distinguish AI outputs from rep entries at a glance.

What We Build

Purpose-built features for your industry.

Activity-based lead scoring

Claude reads email threads, call log content, meeting notes, and engagement frequency to score leads against your actual ICP -- not a static point system. Scores update automatically as new activity is recorded, without rep input.

Deal summary generation

For any open opportunity, Claude synthesizes recent activity, stakeholder interactions, and stage history into a concise deal brief written back into a Salesforce rich text field. Your managers read context in 30 seconds instead of clicking through 14 activity records.

Pipeline forecast signals

Claude flags opportunities where activity has dropped off relative to expected close date, where stage age exceeds your historical average, or where sentiment in logged notes indicates deal risk. Signals surface in a Salesforce list view your RevOps team already uses.

Automated follow-up task creation

When a meeting is logged with no follow-up task and no next contact date, Claude creates a structured Salesforce task with a suggested action based on deal stage and last interaction content. Reps see it in their queue the same day.

Built on a Modern, Secure Stack

Claude APISalesforce APISupabaseVercelSlack API

Our Development Process

From discovery to launch. Quality at every step.

01

Salesforce audit and data mapping

1 week

We connect to your org in sandbox, review object structure, field usage, activity log quality, and existing scoring rules. We identify which data is reliable enough to feed the model and which gaps need a workaround before we build.

02

Prompt design and output schema definition

1-2 weeks

We write and test the Claude prompts against real records from your org -- anonymized where needed. You review draft outputs for lead scores, deal summaries, and task descriptions before we write a single line of integration code.

03

API integration build and sandbox testing

2 weeks

We build the integration layer connecting Salesforce and Claude, configure field-write permissions with your admin, and run the full pipeline against a controlled set of records in your sandbox environment. Edge cases are documented and resolved here.

04

Production deployment and RevOps handoff

1-2 weeks

We deploy to production, monitor the first two weeks of output quality with your RevOps team, and deliver documented runbooks so your admin can adjust scoring logic, update prompts, or add new triggers without coming back to us.

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Frequently Asked Questions

AI looks at email opens, page visits, content downloads, meeting attendance, firmographic data -- all of it -- and scores leads based on what your actual closed-won deals look like. Not a generic model. Yours. And because it's learning continuously, it doesn't go stale the way static rules do.
Yes. Point AI at any opportunity and it reads all activities, emails, notes, and stage history -- then hands back a clear summary in about 30 seconds. No more scrolling through months of activity trying to remember where things stand.
AI lead scoring and deal summaries start at $5,000. The full suite -- pipeline forecasting, competitive intelligence, automated follow-ups, the works -- runs $15,000 to $25,000 depending on your Salesforce setup and team size.
It complements Einstein, it doesn't replace it. Claude adds stronger reasoning and natural language understanding -- so you can ask your CRM real questions in plain English and actually get useful answers. Not "here are 47 records." But "the Johnson deal is stuck because legal hasn't reviewed the MSA, and here's what to do about it." That's the level of intelligence we're talking about.
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