AgentforceClaudeOpenAIMCP

An agent is only as goodas the process behind it.

Most failed agent projects are not model problems. They are process problems. We have spent years inside lead-to-revenue, so we know what to automate and what it breaks.

See an agent’s output Talk to the team who built them

agents and automations built

model and orchestration platforms

role-based reports per scan

integrations behind the process knowledge

Why us

We know the business process before we automate it.

Anyone can wire a model to your CRM. The hard part is knowing which decision is worth automating and what breaks downstream when you do. Our functional consultants have run quoting, billing, revenue recognition and renewals inside real businesses, and they work alongside our enterprise architects on every agent we build.

Functional consultants

People who have owned deal desk, month-end close and renewals. They map the process as it actually runs, including the exceptions nobody wrote down.

Quote to cashRevRecRenewalsDeal desk

Enterprise architects

They decide where the agent sits, what it can touch, and how it stays inside the governance your security team already signed off.

ArchitectureData modelGovernanceAccess control

Build and evaluation

Agents are scored against a test set before scope widens, grounded on your records, and kept under human review wherever output leaves the building.

Scored testingGroundingHuman in the loop

Bottom lineProcess knowledge is the moat. The model is a commodity.

The catalogue

What we have built.

Salesforce Org Health Scanner

Custom scanner and LLM reporting

Reads an entire Salesforce org and writes three reports from one scan: developer, project manager and executive. It is one of the tools behind our Salesforce Health Check.

Executive Score

Scoring model with published calculation

Turns a raw scan into one number a board can hold, with every component traceable back to the finding that produced it.

GTM Sales Rep Agent

Agentforce and Data Cloud

Pulls account context, drafts the next touch and keeps CRM current without the rep typing it. Scored against a test set rather than shown as a demo.

Lead scoring and routing

Model Context Protocol

Reasons against live CRM records instead of a stale export, and writes the score back with its reasoning attached so it survives a pipeline review.

Outbound research and drafting

Claude and live signal sources

Researches an account and drafts sequenced outreach a human edits and sends. We run it on our own go-to-market.

Call workflow automation

n8n, telephony and CRM logging

Handles prep, dial, disposition and logging so the hour goes on talking rather than typing.

Delivery operations agent

Jira and internal tooling

Tracks and triages delivery tickets across engagements. Built for ourselves first.

Bottom lineAsk a vendor which process an agent runs on and what happens when it gets an answer wrong. The ones who have built something will have an answer.

Where it pays

Agents earn their seat on the revenue engine.

Marketing

Research the account, draft the campaign, and score the lead before a human ever opens it.

Sales

Account context pulled, next touch drafted, CRM kept current without the rep typing it.

Quote and pricing

Draft the quote, flag the discount that needs approval, keep the deal desk out of email.

Renewals

Surface the account trending wrong while the conversation is still about growth.

Finance operations

Reconcile, explain the variance, draft the entry for a human to approve.

Diligence and audit

Scan an org in hours rather than weeks, with evidence a diligence team will accept.

Salesforce AgentforceClaudeOpenAI Model Context ProtocolSalesforce Data CloudEinstein n8nWorkatoSnowflakeAWS