Acta Legal Recovered 2,000+ Hours Annually with AI Integration
Acta Legal, a law firm of 8 attorneys and 5 support staff, was managing over 500 contracts annually through manual processes. With Corius's AI agent integration, contract review time dropped by 70%, weekly research workload fell from 15 hours to 6 hours, and full return on investment was achieved in 8 months.
Routine processes were handled manually, causing productivity losses worth millions of TRY annually.
AI agent integration — UDA layer, UDF/PDF parser modules, and a Turkish-language semantic search infrastructure.
2,000+ hours saved annually, 15% higher case win rate, full ROI in 8 months.
What Operational Challenges Was Acta Legal Facing?
Acta Legal is an established law firm managing over 200 cases and 500+ contracts annually. Operations such as document review, research, and client communication were largely handled manually. In a structure where the average attorney hourly cost is 4,000 TRY, repetitive tasks had become a significant resource burden.
- UDF files manually downloaded from UYAP and disorganized PDF archives.
- Contract review averaging 10 hours per attorney.
- Legal research workload reaching 15 hours per week.
- Manual responses to client inquiries and requests.
- Delays in tracking the impact of new legislative changes on existing files.
How Did Corius Solve These Challenges?
The AI agent infrastructure built around the UDA layer — with parser modules, semantic search, and LangChain-based agents — automated all document processes across the firm.
The firm's data infrastructure was reviewed. Workshops were held with attorneys and support staff. The UDA layer was designed and KVKK-compliant security layers were planned.
- Mapping of existing data sources (UDF, PDF, SQL, email)
- UDA layer design with RESTful API and GraphQL
- KVKK-compliant OAuth and encryption architecture
- Prioritization of key needs: automated review, smart search, risk monitoring
UDF/PDF parser modules were developed. Full-text and semantic search layers were set up. LangChain-based AI agents were connected to the UDA.
- Python-based UDF parser (UYAP wrapper)
- PDF processing with PyPDF2 and Tesseract OCR
- Full-text search with Elasticsearch
- Turkish legal-BERT fine-tuning + Pinecone vector database
- LangChain-based AI agent integration
The system was tested on a pilot scenario of 50 contracts. Semantic search accuracy was raised above 85%.
- Pilot test: 50 contract scenarios
- Vector search accuracy raised to 85%+
- PDF table extraction improvements
Which Processes Were Automated?
Contract Review and Drafting
Documents were matched against prior contracts via semantic search; the AI agent identified risky clauses and generated drafts.
Legal Research and Case Analysis
Case law was queried via semantic search; research reports were prepared by the AI.
Document Management and E-Discovery
Thousands of documents were automatically classified, filtered, and summarized.
Client Communication Automation
A chatbot was set up to handle basic client queries; complex requests were routed to attorneys.
Compliance Monitoring and Risk Assessment
New legislation documents were scanned and compared against existing files; automatic alerts were sent upon detecting non-compliance.
What Results Did the AI Integration Produce?
Contract reviews used to consume hours of our team's time; with Corius's agent, they're completed in minutes. Our attorneys can now genuinely focus on strategic work.