/ Website and lead generation · PUBLISHED CASE
Infigo Research Laboratories
A discoverability and lead-qualification system for specialist expertise
A specialist consultancy reported a substantial increase in daily website leads after rebuilding its web presence and lead workflow with AI support.
/ THE SHORT VERSION
A specialist consultancy reported a substantial increase in daily website leads after rebuilding its web presence and lead workflow with AI support.
01 / BUSINESS CONTEXT
The work before the tool.
Infigo serves food manufacturers with specialised research and advisory work. Its expertise was difficult to discover online, and the existing website did not provide a clear route from a buyer question to a qualified enquiry.
02 / THE INTERVENTION
What changed in the workflow.
The company used AI to rebuild website content, produce focused pages, structure lead scoring and improve how its specialist knowledge could be found and understood.
The publication reports a live website and lead flow. It does not provide channel-level attribution or a controlled test of the changes.
03 / REPORTED OUTCOMES
The numbers, with their labels attached.
| Workflow area | Before | After |
|---|---|---|
| Discovery | Specialist expertise was difficult to find and navigate | Focused pages explain services and buyer questions more clearly |
| Lead flow | Limited daily inbound and little qualification structure | AI-supported qualification helps organise higher enquiry volume |
| Content control | Pages were slow to prepare | Experts can review a larger number of structured drafts |
Capability matters when people stay in control.
Subject-matter experts remained responsible for technical claims and client fit. AI supported publishing and qualification, while people approved the advice and commercial response.
05 / WHAT A SIMILAR BUSINESS SHOULD TEST
Transfer the pattern, not the conclusion.
- 01
A discoverability system begins with verifiable expertise and buyer language.
- 02
Lead volume should be paired with qualified-opportunity and revenue measures.
- 03
Publishing velocity is useful only when accuracy and distinct user intent are protected.
06 / SOURCE AND LIMITS
What this page can and cannot establish.
This analysis summarises outcomes published in MCCIA’s AI: Compilation of case studies (2026), printed pages 42–43. The work was conducted through the MCCIA Applied AI Studio. The report credits the Studio team managed by Neeraj Thakur, with Gauri Kale and Ismail Patel. The featured organisation is not presented as a dotSuper client.
- 01The lead increase is company-reported and the publication does not separate the effect of AI, the website rebuild, promotion or market conditions.
- 02Page-production volume is not a measure of usefulness, quality or search performance on its own.
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