$1M+

Pipeline Generated

100%

ROI on First Deal

2 min

Research Time

AI-Powered Sales Transformation

How a PE portfolio company scaled outbound pipeline with multi-agent automation

The sales development team at a private equity portfolio company in energy services was stuck in a cycle that every SDR knows too well: 70% of their time went to research and administrative tasks, leaving just 30% for actual selling. Researching a single prospect account took 30 to 45 minutes of manual work across Google, LinkedIn, Salesforce, and their outreach platform. Meanwhile, thousands of dormant accounts sat in Salesforce waiting to be enriched, and multiple decision-maker personas (CFOs, Facilities Directors, Sustainability Leads) needed to be identified at every target company.

As a PE portfolio company with an aggressive growth mandate, the math was simple: they needed to scale outbound activity without proportionally scaling headcount. Hiring more SDRs to do the same manual work wasn't the answer. Automation was.

What We Built

AI Experts designed and deployed a multi-agent AI system that automates the entire prospect research workflow - from initial account identification through personalized outreach. The system handles six core functions: discovering and validating decision-maker contacts via LinkedIn, enriching Salesforce records with verified emails and career history, scoring accounts by creditworthiness and financial viability, qualifying prospects against ideal customer profile criteria, generating personalized email openers based on prospect research, and pushing qualified leads directly into outreach sequences.

The system writes directly to Salesforce with no manual data entry. It runs 24/7, enriching accounts while the team sleeps. And critically, it includes a human-in-the-loop dashboard - a custom web application where the team can review AI-generated updates before they go live in the CRM.

There's no per-seat licensing and no vendor lock-in. The system is custom-coded, owned entirely by the client, and runs at marginal API cost. It connects natively to their existing stack: Salesforce, ZoomInfo, Outreach.io, and LinkedIn.

The Results

The impact was immediate and measurable. Account research time dropped from 30-45 minutes to under 2 minutes per account. The system began enriching thousands of dormant Salesforce accounts weekly with verified contact information, financial qualification data, and personalized outreach messaging.

More importantly, the system generated real revenue. It produced over $1M in qualified pipeline, and the first closed deal - an enterprise contract with a major healthcare client - fully covered the entire investment. That's 100% ROI before any additional deals even close. Every future deal is pure upside on an investment that has already paid for itself.

The operational transformation was just as significant. SDRs went from spending most of their day on research to spending most of their day on what they were hired to do: building relationships and closing deals. The sales team now wakes up to qualified leads, not research tasks.

Why It Worked

This wasn't a generic SaaS tool bolted onto their workflow. Four things made it succeed where off-the-shelf solutions had fallen short:

• Full-stack integration. The system connected seamlessly to Salesforce, ZoomInfo, Outreach.io, and LinkedIn. It wasn't a point solution - it was the entire research workflow, automated end-to-end.
• Industry-specific design. The qualification criteria, scoring models, and outreach templates were purpose-built for their target market: healthcare facilities and large commercial properties.
• Financial qualification built in. API partnerships with credit providers meant the sales team only pursued creditworthy prospects, eliminating wasted effort on accounts that would never close.
• Client ownership. This is a custom-coded system that the client owns outright. No subscription fees, no per-seat pricing, no dependency on a vendor's product roadmap. It runs at marginal API cost and evolves on their terms.

This case study has been anonymized. Metrics and outcomes are accurate to the engagement.