Contract management · Production

QIMA cuts contract upload and tagging time by 75% and automates data extraction with Juro

The problem

QIMA's lean legal team was drowning in manual contract work, with clunky legacy tools, slow uploads, and scattered data that could not keep pace with the business's growth.

First attempt

The legacy contracting tool bundled into QIMA's ERP required everything to be typed in by hand, had poor UX, and was not built for modern team workflows.

Workflow diagram · grounded in source
1
Automated contract ingestion
integration
“Juro's data-rich contract repository slashed the hours the team previously spent uploading, tagging, and filing documents”
2
AI data extraction
ai_action
“Data extraction is one of the most repetitive tasks we handle. Our team uses it on every contract, saving hours of work and greatly improving data quality.”
3
Searchable contract repository
output
“every contract automatically lives in the platform and is fully searchable by default”
4
Signatory link for signatures
output
“The option to send a simple link to the signatory has been amazing”
5
Payment letter template
output
“the team created a simple, non-negotiable payment-letter template in Juro. The impact was immediate: clients responded faster, and QIMA recovered a considerable amount in overdue payments within a short period”
Reported outcome

QIMA cut contract upload and tagging time by 75%, automated data extraction from third-party contracts with AI Extract, eliminated the signature-chasing bottleneck, and recovered a considerable amount in overdue payments using a Juro payment-letter template.

Reported metrics
Contract upload and tagging time75 per cent
Time previously spent uploading contracts per weektwo or three hours every week
Data extraction time savedsaving hours of work
Data quality improvementgreatly improving data quality
Show all 5 reported metrics
contract upload and tagging time75 per cent
time previously spent uploading contracts per weektwo or three hours every week
data extraction time savedsaving hours of work
data quality improvementgreatly improving data quality
overdue payment recoveryconsiderable amount in overdue payments
Reported stack
JuroAI Extract
Source
https://juro.com/case-studies/qima
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

QIMA cut contract upload and tagging time by 75%, automated data extraction from third-party contracts with AI Extract, eliminated the signature-chasing bottleneck, and recovered a considerable amount in overdue payme…

What tools did this team use?

Juro, AI Extract.

What results were reported?

Contract upload and tagging time: 75 per cent; Time previously spent uploading contracts per week: two or three hours every week; Data extraction time saved: saving hours of work; Data quality improvement: greatly improving data quality (source-reported, not independently verified).

What failed first in this deployment?

The legacy contracting tool bundled into QIMA's ERP required everything to be typed in by hand, had poor UX, and was not built for modern team workflows.

How is this contract management AI workflow structured?

Automated contract ingestion → AI data extraction → Searchable contract repository → Signatory link for signatures → Payment letter template.

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