Case Study: Biometrics — Lead Intel in 90s

Sales teams do not have a research problem. They have a capacity problem. When a rep spends thirty minutes per lead figuring out who the prospect is, what they care about, and which colleague should pick the lead up, that is thirty minutes that did not go on a conversation.

This case study walks through what happened when a global biometrics leader replaced their manual lead routing and research process with an AI-powered lead intelligence system. The brief was simple: keep the reps fully in control of customer relationships, but give back the hours that disappeared into research and triage. The result was lead intelligence delivered in 90 seconds, across 8 reps and 6 regions.

What was the lead intelligence bottleneck for a global sales team?

FPC is a leading global biometrics company providing fingerprint sensors and iris recognition solutions to device manufacturers worldwide. With sales reps covering EMEA, Americas, China, Japan, India, and APAC, they had a lead routing and qualification problem sitting underneath a much bigger capacity problem.

Every inbound lead, whether from the website, an event, or a manual entry, required 30+ minutes of work before a rep could respond:

• Manual routing: which of the eight reps should handle this enquiry?
• Manual research: company background, recent news, funding signals
• Manual qualification: which region, which product line, hot prospect or early researcher?
• Manual drafting: writing a relevant first response from scratch

The result was leads sitting in the queue while reps figured out who should respond. Hot prospects risked going cold while waiting for follow-up. Valuable selling capacity was consumed by research instead of conversations.

This was not a speed problem. It was a capacity problem.

Where the time went	Per inbound lead
Manual routing	Triage decision across 8 reps and 6 regions
Manual research	Company background, news, funding signals
Manual qualification	Region, product line, hot vs cold
Manual drafting	Personalised first response from scratch
Total	Around 30 minutes before a conversation could start

With eight reps covering FPC sales globally and multiple product lines, the research and qualification work simply could not scale. Every hour spent researching companies was an hour not spent having sales conversations. Salesforce's State of Sales research has consistently found that reps spend less than a third of their week actually selling, and this case is a textbook example of where the rest goes.

VP Channel and Marketing Gonzalo de Gisbert was managing not just global marketing but coordinating the distribution of leads, ensuring they reached the right person fast enough to convert interest into action. The system that handled that triage manually was about to become the constraint on growth.

What did we build to deliver lead intelligence in 90 seconds?

We built an AI-powered Lead Intelligence System that researches, qualifies, routes, and drafts responses for every inbound lead in 90 seconds.

The automation handles:

• Company research: recent news, press releases, funding information, website details (products, services, structure)
• Lead scoring: analyses enquiry message for sentiment, intent, and urgency (hot prospect vs early researcher)
• Smart routing: matches lead to the right rep based on geography and product expertise (a fingerprint sensors opportunity in EMEA, an iris recognition project in Americas, and so on)
• Draft response: writes a personalised first email ready for the rep to review and send

Sales reps receive:

• A complete intelligence brief in their inbox within 90 seconds
• Lead score and priority flag (hot leads marked for immediate attention)
• All research context (no need to Google the company)
• Draft email ready to personalise and send

Humans still control:

• Reviewing the draft response before sending
• Deciding when and how to follow up
• Building the actual relationship

The system pulls from multiple sources (website forms, event registrations, manual entries) and processes everything through one intelligent pipeline. The pattern is the same human-in-the-loop design we use across every sales automation we ship: AI handles the heavy lifting on research and drafting, humans keep the final say.

What changed after the lead intelligence system went live?

Metric	Before automation	After automation
Lead intelligence delivery	30+ minutes	Under 90 seconds
Per-rep capacity reclaimed	Crowded out	2+ hours per day for selling conversations
Hot lead response time	Hours to days	Within the hour
Routing accuracy	Manual triage, error prone	Automated, expertise-matched
Lead prioritisation	Gut feel	Clear lead scores per enquiry
Scaling cost	Linear with lead volume	Flat

The headline number is 90 seconds. The more interesting number is the 2+ hours daily per rep that came back. McKinsey's analysis of how AI is reshaping sales productivity is consistent with what FPC has seen: the lift compounds across the funnel because reps spend more time on conversations and less time assembling context. HubSpot's State of Sales research reaches a similar conclusion from a different angle, finding that reps spend a small minority of their week actually selling, with most of the rest going on exactly the kind of context-assembly work this automation removes.

Why this worked for a distributed global team

Solved the capacity problem. FPC did not just need faster research. They needed research capacity that could scale across eight reps and six regions without hiring a dedicated research team. The automation provided the capacity that was not there before.

Built for complexity. Eight reps, six regions, multiple product lines. The routing logic handles all of it automatically, matching expertise to opportunity every time. Adding the ninth rep or a new product line is a configuration change, not a rebuild.

Speed with context. Getting leads to the right person fast matters, but so does giving them the intelligence to have an informed conversation immediately. Both problems solved in one pipeline, not two separate tools.

Reps love it. The team has already started asking how to apply the same intelligence layer to their existing lead database. When sales reps ask for more automation, it is a good sign the first deployment landed.

Instant payback. Capacity unlocked across the entire team meant the build paid for itself in weeks, not months. The model maps cleanly onto the 30/60/90 day automation roadmap pattern we use with every new client.

Client testimonial

"Research and qualification consumed hours every day for our team. This was valuable time that should have been spent on conversations. Now the right rep has everything they need within 90 seconds: company background, lead score, and a draft response. Hot prospects get informed responses within the hour. And when we go to events, the reps can also use this automation for providing all the background research for when they get back to their desk and start the follow-ups. For a global team covering multiple time zones and product lines, this has transformed how we follow up with leads."

Gonzalo de Gisbert, VP Channel and Marketing, FPC

What this means for your sales team

If you have a distributed sales team handling leads across regions, products, or time zones, you are facing the same challenge. You do not have a speed problem. You have a capacity problem.

Your sales team has the expertise to close deals. If research and qualification consume their capacity, those conversations will not happen. Automation solves the capacity problem without taking the human relationship work off the rep. For the upstream version of this conversation, the hidden cost of manual RevOps walks through how to spot the same pattern in your own pipeline before it becomes the constraint on growth.

Technical implementation

For teams interested in how this works:

Built on n8n workflow automation, integrating FPC's CRM, OpenAI GPT (message analysis and draft generation), Brave Search API (company news and funding research), and Firecrawl (website data extraction). Intelligent routing logic handles 8 reps across 6 regions and multiple product lines. Everything processes in under 90 seconds from lead creation to intelligence delivery.

Frequently asked questions

What is an AI lead intelligence system?

An AI lead intelligence system researches an inbound lead end-to-end: pulling company background, recent news, funding signals, and website context, then scoring intent and routing the lead to the right rep with a draft response ready to send. The point is to give the rep everything they need to have an informed first conversation without spending 30 minutes assembling the brief themselves.

How long does AI lead research take compared to manual?

Around 90 seconds end-to-end, against 30+ minutes of manual research, qualification, routing, and drafting. The 95% reduction is consistent across our deployments because the bottleneck was never the AI's reasoning speed, it was the human cost of switching between five different tabs to assemble a single lead brief.

Can AI route leads across multiple regions and product lines?

Yes. The routing logic combines geography, product expertise, and inferred intent from the inbound message to match each lead to the right rep automatically. For FPC the system covers 8 reps, 6 regions, and multiple product lines (fingerprint sensors, iris recognition), with no manual triage step in between. Adding a region or a product line is a configuration change, not a rebuild.

What does human-in-the-loop sales automation look like?

AI handles the research, scoring, routing, and draft response. The rep reviews the brief and the draft, then decides how to follow up and what relationship to build. The automation never sends a message on the rep's behalf without explicit approval. That keeps tone, judgement, and accountability with the human while reclaiming the hours that used to go on assembling context.

How long does it take to build a lead intelligence system like this?

Six to ten weeks from kick-off to production for a typical UK SME deployment, including discovery, integration with the CRM and inbound sources, the AI research pipeline, the routing logic, and rep training. The schedule mirrors the standard 30/60/90 day phasing for UK SME automation, with the build itself usually taking three to five weeks once the scope is locked.