How Avinmont built an AI agent that researches every prospect like a senior BD analyst.
A business-development agent that turns a target list into pitch-ready intelligence. For each person, it reads their website, pulls their LinkedIn, scans the company's news, and builds a full research profile: the kind of preparation a senior BD analyst would take an afternoon to produce for a single name. Avinmont has run it across more than thirteen thousand prospects to date.
Five minutes per prospect, versus two days by hand, and the outreach actually lands.
Situation
Cold outbound has the same failure pattern everywhere. The research never happens. Teams are supposed to spend an hour per prospect reading their website, understanding their company, reviewing their LinkedIn profile, finding the angle that matters to that specific person. Nobody does. What goes out instead is a first-name-token template, and the reply rate collapses to nothing.
The question Avinmont Strategy brought to this engagement was whether the research step could be done by a custom AI agent: at quality, at volume, every time, without a human having to remember to do it first.
Approach
Arjun Khinvasara led the design of a multi-stage research pipeline. The agent pulls the prospect's website, scrapes their LinkedIn profile using persistent sessions so the system does not need to authenticate again every few minutes, scans the company's news and public filings, and builds a structured research profile for each person. From there, a classifier assigns a prospect archetype based on what the research reveals. A strategist layer picks the angle, the salutation, the language complexity, the framing. The outreach itself is drafted in a voice tuned to what matters to that specific person, not to a template. Every send is gated behind a human approval step. Nothing leaves the system without someone signing off.
The infrastructure is intentionally simple. A single VPS, a staged pipeline, cost-optimized models for the research summarization layer, quality-critical models for the strategy and writing layers. No microservices. No overbuilt architecture. The engineering cost to run it is a small fraction of the value the outreach generates.
Result
More than thirteen thousand prospects researched end-to-end to date, spanning recruiting firms, fintech boutiques, industrial service businesses, and professional services. Each prospect receives a full research wiki, a classifier archetype, and a three-email sequence tuned specifically to them. The five minutes of work the agent does per prospect would cost a team two days by hand, and most teams do not do it at all, which is why their outreach lands without context and gets no reply.
Avinmont's own outreach lands with context every time, because the research is always done. Every email feels like it was written for the person receiving it, because it was.
What This Proves
The bottleneck in cold outbound is not the writing. It is the research. Once the research is automated, at quality, at volume, the writing becomes the easy part. Every email ends up personal because the system always has the material to make it so.
This is the pattern Avinmont Strategy applies broadly. Find the step in the workflow where humans always cut corners. Automate that step first. The rest of the workflow gets better on its own.
Want your BD team's research done for them, every time?
Tell Avinmont Strategy about it. Thirty-minute call. We will tell you honestly whether a custom AI agent is the right answer, what it would cost, and how long it would take. Most builds land between four and eight weeks.
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