/ 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.

Food manufacturing consultancySpecialist consultancySource pages 42–43
MCCIA-PUBLISHED CASEANALYSED BY DOTSUPERNOT PRESENTED AS A DOTSUPER CLIENT

/ 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.

THE OPERATING CONSTRAINTContent production was slow, the website did not reflect the depth of the offer, and incoming interest was not supported by a structured qualification flow.

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.

DEPLOYED VS. PLANNED

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.

~1 → 22website leads per dayReported by the organisation in the MCCIA publication. Not independently audited.
20+pages produced per dayReported by the organisation in the MCCIA publication. Not independently audited.
Before and after, based on the published case narrative
Workflow areaBeforeAfter
DiscoverySpecialist expertise was difficult to find and navigateFocused pages explain services and buyer questions more clearly
Lead flowLimited daily inbound and little qualification structureAI-supported qualification helps organise higher enquiry volume
Content controlPages were slow to prepareExperts can review a larger number of structured drafts
04 / HUMAN CONTROL

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.
Read the original MCCIA publication
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