Trench Group cuts contract review times 80% with Luminance AI

Trench Group deployed Natural Language Processing for Contract Review & Analysis in Corporate Legal & In-House. As reported by itbrief.co.uk: 80% (150 min → 30 min) contract review time reduction.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
80% (150 min → 30 min)Contract Review Time Reduction
80%Contracts Handled Without Legal Team
2.5 weeks → under 2 hoursTariff Analysis Time

Source-reported figures — cited source: itbrief.co.uk

Trench Group
Metric Before After Impact
Contract review time 150 min/contract 30 min/contract 80% reduction
Contracts handled without legal team — 80% Majority self-served
Tariff impact assessment (700 contracts) 2.5 weeks Under 2 hours ~99% reduction

What Trench Group was trying to fix

As a high-voltage component manufacturer operating across sales, operations, and procurement functions, Trench Group faced a contract approval process that had become a significant operational bottleneck. Routine agreements consumed an average of 150 minutes of legal review time each, requiring direct involvement from qualified lawyers regardless of contract complexity or risk level. This created downstream delays in commercial decision-making and left the legal team with limited capacity for higher-value strategic counsel. With the volume of contracts spanning multiple business functions, the risk of missing critical obligations or overlooked exposures was compounded by the manual, time-intensive nature of the process.

What Trench Group deployed

Trench Group deployed Luminance's AI platform — developed by the Cambridge-based legal AI company — to automate the initial stage of contract review using Natural Language Processing. The system reads incoming contracts, identifies clauses that deviate from Trench Group's corporate standards, flags potential risk exposures, and surfaces suggested mitigations for the reviewing user. Rather than replacing legal oversight entirely, the platform introduced a triage model: non-legal teams in sales and operations can self-serve on standard agreements, with the legal department engaged only when the AI surfaces high-risk or complex issues. This created a centralised, auditable workflow that reduced manual intervention without sacrificing risk visibility, giving the legal team a single source of truth across the company's entire contract portfolio.

Results

Contract review time dropped from 150 minutes to 30 minutes per contract — an 80% reduction — with approximately 80% of contracts now processed without initial legal team involvement. The impact on time-sensitive analysis was equally significant: a tariff impact assessment across 700 contracts, previously requiring two and a half weeks of manual work, was completed in under two hours using Luminance's platform. Qualitatively, the legal team shifted from document processing to strategic counsel, and management gained faster access to evidence-based commercial insights. Tim Siewert-La Chon, Head of Legal at Trench Group, noted the team now has "complete visibility into obligations and the confidence to make faster decisions."

Key Takeaways

  • Triage by risk, not by default: routing only high-risk contracts to legal review — rather than all contracts — is what unlocks both speed and legal team capacity.
  • NLP-based contract review delivers compounding value: the same system that handles routine approvals can be repurposed for time-sensitive portfolio-wide analysis, as the tariff assessment demonstrated.
  • Non-legal adoption requires clear guardrails: enabling sales and operations teams to self-serve only works when the AI is configured against defined corporate standards and deviation thresholds.
  • Broader industrial context matters: with over 70% of German manufacturers planning AI investment, legal operations automation is becoming a competitive baseline, not a differentiator.

Evidence for Trench Group's Contract Review & Analysis deployment

Reported outcome metrics
3 cited below
Cited source
itbrief.co.uk
Last updated
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Company Size
MidMarket

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