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CRM Automation & AI Lead Scoring

B2B Sales2026

100%Auto Research

98%Data Accuracy

8 daysDelivery

The Overview

A system that automatically filters and prioritizes the incoming stream of orders. Result: the sales department is freed from information noise. We automated the process of collecting and verifying data, so the team focuses exclusively on closing deals with quality leads.

The Challenge

B2B managers spend hours researching companies manually to figure out if they are "big enough" or worth the call.

The sales team was flooded with inbound leads, but quality was inconsistent. Sales development representatives (SDRs) spent 30-40% of their day manually researching prospect websites, checking LinkedIn employee counts, and estimating revenue just to decide who to call. This "research lag" created two major issues: hot leads weren't contacted immediately while interest was high, and valuable talent was wasting time on dead-end inquiries instead of closing deals.

Initial Concept & Wireframes

The Solution

Automated research agent that uses web-search to score companies from 0-10 and enriches CRM entries before the manager even logs in.

We built an automated enrichment and scoring pipeline that acts as a 24/7 digital analyst. Now, the moment a lead enters the CRM (Pipedrive), a webhook triggers our AI agent to start working. The agent uses Perplexity API and Google Search to perform a "deep dive" on the company. It analyzes their website, identifies key decision-makers, estimates company size, and checks for recent news signals. It then assigns a lead score (0-10) based on the client's Ideal Customer Profile (ICP) and pushes a concise 3-bullet summary directly into the CRM deal notes, allowing reps to start every call fully informed.

Architecture

System Architecture Diagram

Impact

Problem30 mins research/lead

Solution0 mins (Automated)

ProblemSubjective guessing

SolutionData-driven scoring 0-10

ProblemCold outreach

SolutionWarm, informed starts

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