Case Studies

Real documents. Measurable results.

Six organisations across finance, legal, healthcare, insurance, logistics and the public sector — and what changed when their documents started thinking for themselves.

Before and after: a crumpled handwritten paper invoice transformed into a crisp structured digital table

The DocuMind difference

Every engagement starts with a pile of paper and ends with a queryable dataset

The pattern is consistent across every customer: documents arrive as they always have, but the work behind them disappears. Below, six of those transformations — with the numbers to prove them.

Customers

Six transformations, start to finish

Northgate Mutual

Financial Services · Leeds

From three days to four hours: loan application processing

3 days → 4 hrs

Application turnaround

96.1%

Straight-through processing

11 FTE

Hours redeployed to advisory work

The challenge

Northgate Mutual, a Leeds-based mutual bank, received 1,400 SME loan applications a month — PDFs, scans and posted forms — each requiring two staff to key data into the underwriting system.

The DocuMind solution

DocuMind now classifies every incoming application, extracts applicant details, financials and supporting statements, validates figures against internal rules, and posts structured records directly to the underwriting platform.

”Our underwriters now spend their day underwriting, not typing. DocuMind paid for itself inside the first quarter.”

— Helen Marsden, Head of Lending Operations

Fairfax Hale LLP

Legal · Leeds

4,200 legacy contracts made searchable in six weeks

4,200

Contracts processed in 6 weeks

99.2%

OCR accuracy on 1990s scans

£310k

Renewal value protected in year one

The challenge

Fairfax Hale held 4,200 client agreements as scanned PDFs in a shared drive. Finding renewal dates, liability caps or notice periods meant an associate reading contracts manually.

The DocuMind solution

DocuMind OCR read the full archive, classified each agreement type, extracted parties, key dates and commercial terms, and populated a searchable contract register with clause-level source links.

”We found three auto-renewals we would have missed. The register alone justified the entire project.”

— Daniel Okonjo, Partner, Commercial

Vale of York Health Partnership

Healthcare · York

Automating 78% of referral triage coding

78%

Referrals auto-coded

4.2 hrs

Saved per coder, per day

Urgent referrals missed since launch

The challenge

Referral letters from 140 GP practices arrived in every format imaginable — typed, handwritten, faxed. Clinical coders manually read each one to assign specialty and urgency.

The DocuMind solution

DocuMind reads each referral, extracts presenting complaint, urgency markers and patient identifiers, classifies to specialty, and routes urgent cases to the top of the queue — with full audit trails for clinical governance.

”Urgent referrals now surface before a human ever opens the envelope. That is not efficiency — that is patient safety.”

— Dr Priya Raghunathan, Clinical Director

Ridings Assurance

Insurance · Harrogate

62% faster claim intake for a specialist insurer

62%

Faster intake handling

94.7%

Field extraction accuracy

< 15 min

Email to open claim file

The challenge

Ridings handles equine and agricultural insurance. Claims arrive as FNOL forms, vet reports, photographs and broker letters — often all mixed in one email thread.

The DocuMind solution

DocuMind splits mixed packets, classifies each document, extracts claim and policy details, validates against policy schedules, and opens the claim file in the core system with every attachment linked and categorised.

”Our handlers now start with a complete, structured claim file instead of an unread email thread.”

— Tom Braithwaite, Claims Director

Ouse Valley Logistics

Logistics · York

1,900 hours a year of POD keying, eliminated

1,900 hrs

Keying time saved per year

97.4%

Handwriting read accuracy

92%

PODs auto-matched to jobs

The challenge

Drivers photographed 2,300 signed delivery notes a week on handhelds — rotated, shadowed, handwritten. Back-office staff keyed every one into the TMS to close jobs and invoice customers.

The DocuMind solution

DocuMind pre-processes each photo, reads the handwriting, extracts consignment, signature and exception notes, matches to the job, and closes it in the TMS. Exceptions route to a small review queue.

”Photographed, on the dock, at 6pm — and the job is closed before the driver gets home.”

— Karen Sutcliffe, Operations Manager

City of York Council

Public Sector · York

Planning application registration time, halved

51%

Faster registration

37,000

Attachments classified per year

98.1%

Classification accuracy

The challenge

Planning applications arrived with 15–40 supporting documents each: forms, plans, heritage statements, correspondence. Registration officers manually identified and filed every attachment.

The DocuMind solution

DocuMind classifies every attachment against the council taxonomy, extracts application reference and applicant details, flags incomplete submissions automatically, and files everything to the planning system.

”Incomplete applications are now caught on day one instead of week three. That changes how we serve residents.”

— Michael Errington, Head of Development Management

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