Regulatory Data Engineering & Operations / Case study
Corlytics.
Engineering the data behind regulatory intelligence.
A 40+ member dedicated team supporting Corlytics since 2022 through Python data collection, processing, content operations, quality validation and backend support.
- Dedicated professionals
- 40+
- Partnership established
- 2022
- The challenge
- Regulatory information arrives through varied websites, document formats and publishing structures. Corlytics needed sustained support to collect, process, review and validate this information as source structures and business requirements changed.
- Our contribution
- Engross established a dedicated team working as an extension of Corlytics’ organization, covering business analysis, Python scraping, data processing, content editing, quality validation, backend support and Jira-based delivery coordination.
- The outcome
- A continuing 40+ member multidisciplinary engagement since 2022, providing operational capacity, accumulated process knowledge and coordinated support for regulatory data workflows. Automation, business understanding and human judgment work together within one delivery model.
- Technology & tools
- Python · Web data scraping · Data processing · Jira
What the work involved
- Business analysis: clarify requirements and business rules, define practical workflows, and connect business stakeholders with engineering, data and content teams.
- Python data collection: develop and maintain source-specific scraping logic, including extraction, parsing, transformation, error handling and changes to source websites.
- Data processing and backend support: support automated processing workflows and engineering requirements that prepare information for downstream handling.
- Content operations: review, edit, structure and enrich regulatory information using the required formats and contextual human judgment.
- Quality and validation: combine automated checks with human review to identify missing information, extraction errors, formatting inconsistencies and content issues.
- Delivery management: use Jira to organize requirements, tasks, priorities, issues and work allocation across the engagement.
From regulatory source to reviewed content
- Source discovery
- Data extraction
- Processing
- Analysis
- Content editing
- Validation
- Intelligence support
About the client
Corlytics provides an AI-powered regulatory intelligence platform that helps regulated organizations monitor regulatory developments and manage regulatory risk. Its public solutions span regulatory monitoring, regulatory change, obligations and policy management.
The operating model
Corlytics provides regulatory expertise, product direction and business requirements. Engross contributes business analysis, engineering, data, content and quality capabilities that support the agreed operating processes.
Automation handles repeatable collection and processing tasks. Business analysts and content specialists bring context to complex information. Quality specialists review outputs and investigate exceptions, while delivery management keeps priorities and responsibilities visible.
Business value
- Dedicated capacity
- A 40+ member multidisciplinary team supports technical and operational requirements within one continuing engagement.
- Continuity since 2022
- Long-term collaboration builds domain knowledge and familiarity with Corlytics’ requirements, processes and workflows.
- Repeatable operations
- Python-based automation supports recurring data tasks, with collection logic maintained as sources evolve.
- Quality and adaptability
- Structured human review helps identify issues, while processes and responsibilities respond to changing sources and business requirements.
- Delivery visibility
- Jira connects requirements, issues, priorities and progress across business, engineering, content and quality teams.