Building an Always-On Prospecting Engine with Agentic AI

Challenge

Freese Project Solutions, a Twin Cities professional services business providing Owner’s Representative services to manage corporate tenants’ office-space buildouts from architect selection through move-in, had a go-to-market strategy driven by referral relationships. When a company signs a lease on new office or light-industrial space, the buildout that follows is Freese’s service window, and the broker who closed that lease is the path to a new customer. But the firm had no dedicated business-development capacity yet, so deal announcements surfaced and expired unseen, the brokers behind them went unmapped, and the short window between a lease signing and the assembly of a buildout team closed without a conversation. The firm needed the market watched, understood, and turned into warm, well-timed introductions, without adding headcount.

Approach

Trexin’s first move was strategic, not technical: embracing the notion that the broker, not the tenant, is really the ongoing prospect, and recognizing that a broker’s lease announcements are the triggering event to reconnect with that broker. After all, a tenant lead is consumed once, but a broker relationship produces referrals for years. That framing shaped Trexin’s whole solution approach: every detected deal now enriches a permanent broker intelligence graph first and generates outreach second, and lease announcements (when buildouts are usually not yet staffed) outrank construction permits (when a buildout team has typically already been hired) as sales-triggering signals.

Trexin built the solution on an agentic AI architecture using Anthropic’s Claude Managed Agents: four cooperating agents (a daily signal scout, a lead curator, a weekly brief builder, and an on-demand deal-brief generator) sharing persistent Claude memory stores for the deal log, the broker graph, and a read-only playbook holding every business rule, including a scoring rubric, a source whitelist, outreach rules in the Client’s voice, and hard AI guardrails.

Intentionally, broker outreach is never sent automatically; every communication is presented as a fully written draft for Freese’s team to review and personally send. And the solution’s user interface is deliberately just email. A weekly brief and same-day hot-lead alerts arrive in the user’s regular inbox, and the user replies to any brief or alert in their own natural language, which the agentic system parses back into its memory, adjusting status, tactics, and strategy accordingly. No new app to learn, no CRM to feed.

Outcome

On its first day of scanning public sources for lease announcements, Trexin’s agentic AI solution surfaced 10 qualified deal signals, built 18 structured broker-intelligence dossiers, and produced one outreach-ready hot lead: a 29,000-square-foot Class A prelease with the buildout window open, the tenant-rep broker identified, and a broker outreach message drafted in the Freese team’s own voice. The solution also discovered a warm entry path when it recognized that one of Freese’s existing broker relationships was named on a live deal in the same building, surfaced automatically by the broker graph.

The core pipeline was validated in the first build week against a written verification checklist, and the complete two-way email interface was live four days later. The system now runs unattended on schedule in the Client’s own environment. Total agent compute for the entire bootstrap-and-validation day was about $11.50, and steady-state operation runs $40 to $60 a month, which is effectively the working capacity of a business-development analyst for less than the cost of one business lunch.

“I went from hoping the right deal crossed my radar to opening a Monday email that already knows my market: which deals are live, which brokers are behind them, and what I should say to them. It’s business-development capacity we simply didn’t have before.”

Ben Freese, Founder, Freese Project Solutions

Why Trexin

Organizations whose demand signals appear in public announcements, from real estate services and construction trades to advisory, staffing, and commercial insurance, share this shape: the deal is public, the window is short, and the relationship is the durable asset. Trexin brought the strategic reframing that shaped the system, the production disciplines that made it trustworthy (human-in-the-loop gates, audited guardrails, provenance on every fact), and the engineering to take an agentic AI system from kickoff to unattended operation in weeks. We get enterprise AI from pilot to production.