Company Profile
Company: Burness Paull LLP Industry: Professional Services / Legal (commercial law firm) Size: ~670 employees (mid-sized regional firm) Location: Scotland (Edinburgh, Glasgow, Aberdeen offices) Practice Areas: M&A, corporate finance, real estate, employment law, litigation, banking
The Challenge
Burness Paull faced a common problem in legal services: Data Subject Access Requests (DSARs) under GDPR were resource-intensive and often unprofitable:
- Volume challenge: A single DSAR required reviewing 6,000+ documents for a former employee request
- Staffing inefficiency: Traditional review required multiple staff members working for extended periods
- Profitability concerns: The time investment often exceeded what could be reasonably billed, making DSAR work economically unviable
- Remote work complications: COVID-19 disrupted workflows mid-project, requiring immediate adaptation
The firm needed to find a way to handle these legally required requests without losing money on every engagement.
The Solution
Burness Paull deployed Luminance AI's document analysis platform:
Technology Stack
- Luminance Diligence - AI-powered contract review and analysis
- Luminance Discovery - eDiscovery and document review platform
- LITE Engine - Luminance's Legal Inference Transformation Engine for pattern recognition
Implementation Approach
Rather than requiring lawyers to read every document, Luminance's AI:
- Ingested the full document set (6,000+ documents)
- Applied machine learning to identify relevant patterns and categories
- Culled irrelevant documents automatically based on learned criteria
- Flagged priority items for human review
- Enabled cloud-based access when COVID-19 forced remote work mid-project
Quantified Results
| Metric | Traditional Approach | With Luminance AI | Improvement |
|---|---|---|---|
| Document review time | Baseline (multiple weeks) | 50% faster | Half the time |
| Initial culling | Manual review of all docs | 80% culled in minutes | Immediate reduction |
| Staffing required | Multiple staff members | Single associate | Dramatic efficiency |
| Profitability | Often unprofitable | Economically viable | Business model shift |
The COVID-19 Test
When the pandemic forced remote work mid-project, Luminance's cloud-based deployment allowed the team to continue without interruption. This unplanned stress test validated the platform's operational resilience.
Implementation Details
Workflow Transformation
Before Luminance:
- Receive DSAR request
- Collect all potentially relevant documents (weeks)
- Assign multiple staff to manual review (weeks)
- Identify and redact sensitive information (days)
- Compile response (days)
- Often bill less than cost → unprofitable
After Luminance:
- Receive DSAR request
- Upload documents to Luminance (hours)
- AI culls 80% of irrelevant documents (minutes)
- Single associate reviews AI-flagged items (days, not weeks)
- AI assists with pattern identification for redaction
- Compile response efficiently → profitable
Key Insight
Samuel Moore, Innovation Manager at Burness Paull, explained the value: "Using Luminance, we are able to comb through large volumes of data in an efficient way, and provide high-level insight into every step of the review."
Why It Worked
1. Targeted Use Case
Rather than trying to apply AI broadly, Burness Paull focused on a specific pain point (DSARs) where the ROI was clear and measurable. This allowed them to prove value before expanding to other use cases.
2. AI Augments, Doesn't Replace
The technology didn't replace lawyers—it eliminated low-value work (reading irrelevant documents) so lawyers could focus on judgment-intensive tasks (identifying sensitive information, making redaction decisions).
3. Immediate Business Impact
Converting unprofitable work into viable services created an obvious ROI that justified further investment in legal AI tools.
Expansion After Success
Following the DSAR success, Burness Paull:
- Adopted Luminance Discovery for all upcoming DSARs
- Implemented Luminance Diligence for M&A due diligence work
- Deployed both platforms across their practice areas
The initial focused implementation created the foundation for broader AI adoption across the firm.
Key Takeaways for Professional Services
- Start with unprofitable work - If you're losing money on certain service types, AI can shift the economics
- Measure staff time savings - "1 associate vs. a team" is a compelling efficiency metric
- Choose domain-specific tools - Luminance's legal focus meant faster implementation and more relevant features than general-purpose AI
- Plan for remote work - Cloud-based AI tools provide operational resilience
- Prove value, then expand - Success with DSARs justified investment in broader legal AI adoption
Want Similar Results?
If document review, due diligence, or compliance work is consuming disproportionate resources at your firm, AI-powered legal technology can dramatically shift the economics.
Next steps:
- Book a working session to assess your document-intensive workflows and identify automation opportunities
- Discuss which legal AI platforms align with your practice areas and security requirements
Typical timeline: Legal AI implementations typically require 4-8 weeks for initial deployment, with ongoing optimization as the system learns your firm's patterns.