Case studies

Implementation, evidenced.

The examples below are clearly labelled representative engagements that illustrate the shape of Mainfold's AI work — the challenge, the system we build and the outcome it produces.

Representative exampleProfessional Services

AI-Powered Document Management

Challenge: Employees spent a significant part of every week searching through thousands of documents spread across drives and email.
Solution: AI-powered document search, classification, summarisation and retrieval with permission-aware access and cited answers.
Outcome: Faster information discovery, less duplicated work and a single intelligent entry point to company knowledge.

10x

faster document retrieval

70%

less manual searching

Representative exampleEcommerce & Retail

AI Customer Support Automation

Challenge: Support volumes grew faster than headcount, and repetitive order and returns questions dominated the queue.
Solution: An AI support agent connected to order data and the helpdesk, resolving routine tickets and escalating with full context.
Outcome: Routine enquiries resolved instantly, first-response times cut and agents focused on complex cases.

62%

tickets auto-resolved

24/7

coverage without new hires

Representative exampleEcommerce & Retail

AI Ecommerce Operations

Challenge: Catalogue work, marketplace compliance checks and performance reporting were entirely manual across channels.
Solution: Agents that enrich listings, monitor marketplace issues, flag pricing anomalies and produce daily operating summaries.
Outcome: Listings kept current across channels and issues caught before they affected sales.

catalogue throughput

Daily

automated operations reporting

Representative exampleB2B Services

AI Sales Intelligence

Challenge: Sales teams spent hours preparing for meetings and CRM records were incomplete and inconsistent.
Solution: A research agent that builds account briefings from public and internal sources and keeps CRM records enriched.
Outcome: Reps arrive prepared, pipeline data stays clean and prospecting time shifts to selling.

5 hrs

saved per rep each week

90%

CRM field completeness

Representative exampleFinance & Operations

AI Document Processing

Challenge: Invoices and purchase orders arrived in dozens of formats and were re-keyed by hand into the ERP.
Solution: An extraction and validation pipeline that structures documents, cross-checks totals and posts clean data to the ERP.
Outcome: Straight-through processing for most documents, with humans reviewing exceptions only.

85%

documents processed untouched

99%

field-level accuracy target

Representative exampleEnterprise Operations

AI Knowledge Assistant

Challenge: New joiners took months to become productive because process knowledge lived in people's heads.
Solution: An internal assistant grounded in policies, SOPs and system documentation, available in chat and the intranet.
Outcome: Shorter onboarding, fewer interruptions to senior staff and consistent answers across teams.

40%

faster onboarding

source of truth for process questions

Let's talk about your version of this.

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