In today's data-driven world, enterprises across industries are under pressure to centralise, structure, and harness vast volumes of external data to fuel AI initiatives, digital transformation, and smarter decision-making. Yet traditional data harvesting methods often fall short when faced with unstructured sources, fragmented tools, and escalating compliance challenges.
At Merit, we are redefining what's possible with an AI-First Approach to Data Harvesting at Scale. Our recent engagement with a leading construction intelligence company exemplifies how scalable, knowledge-driven data harvesting can empower organisations to achieve operational efficiency, security, and AI readiness.
The Challenge: Fragmented, Unstructured Data at Scale
Our client, which offers a construction intelligence platform for various players and entities in the construction industry, faced multiple hurdles:
- Extracting data from diverse sources: web, on-premise and cloud storage, PDFs, architectural plans, and handwritten notes.
- Processing massive volumes - nearly 2 million documents and 475 local council datasets daily at near real-time frequencies.
- Maintaining real-time ingestion and integration without disruption.
- Structuring unstructured information into analysis-ready intelligence.
Traditional methods simply couldn't scale to meet these demands without compromising quality or speed.
Merit's AI-Driven, Scalable Data Harvesting Solution
We engineered a robust, end-to-end data pipeline combining cutting-edge technologies and best practices:
1. Comprehensive Connectivity and Multi-Source Data Ingestion
- Leveraged a broad spectrum of connectors to seamlessly integrate structured (APIs, databases) and unstructured (PDFs, Word, HTML) data.
- Enabled real-time and batch data processing through event-driven ingestion pipelines.
2. AI-Driven Web Scraping Framework
- Built on Python/Scrapy with AI-powered dynamic crawling that adapts to site structure changes.
- Integrated evasion techniques such as proxy rotation, CAPTCHA solving, and browser fingerprinting to ensure uninterrupted, ethical data extraction.
3. Advanced Entity Recognition for Contextual Enrichment
- Utilised NLP models and machine learning techniques to extract key entities like project names, locations, stakeholders, and deadlines from unstructured text.
- Continuously improved entity recognition to enrich the knowledge graph and boost the quality of insights.
4. Knowledge Graphs for Actionable Intelligence
- Mapped relationships across disparate datasets to build a robust, query-able knowledge graph.
- Enabled the client to move from isolated data points to interconnected intelligence, unlocking new insights for smarter decision-making.
5. Configurable Python-Based Rules Engine
- Developed a highly flexible rules engine to adapt quickly to new data types and evolving use cases.
- Applied dynamic validation, transformation, and enrichment rules with ease, ensuring the pipeline stayed agile and responsive.
6. Compliance and Governance Toolkit
- Embedded GDPR, CCPA, and sector-specific compliance frameworks to ensure ethical and secure data operations.
- Automated data lineage, transformation logging, and audit tracking for complete transparency and governance.
7. Deployment Flexibility: Cloud or On-Premise
- Delivered a solution deployable on cloud-native platforms or on-premise environments based on client needs.
- Leveraged Kubernetes and scalable architectures to ensure reliability, cost efficiency, and enterprise-grade security.
Considering the construction intelligence firm was offering a ‘Data as a Product’ platform solution, we gave them a modern data solution that was deployed on the web, but the flexibility was critical to have.
Why Merit? Our Edge in Data Harvesting
At Merit, we bring to the fore the following:
- 20+ years of expertise in large-scale, AI-powered data implementations.
- AI-driven web scraping, cleansing, enrichment, and knowledge graph construction.
- Open-source foundations enabling rapid customisation and seamless enterprise integration.
- Practical AI deployment reducing manual effort and accelerating time-to-value.
- Proven success across financial services, retail, healthcare, and construction intelligence sectors.
Addressing Key Enterprise Needs with our Data Harvesting Solution
For today's Data & AI Leaders, Digital Transformation Champions, and Business Intelligence Teams, Merit offers:
- Automation at Scale: Eliminate manual data collection bottlenecks.
- AI-Ready Datasets: Fuel predictive analytics, AI/ML initiatives, and smarter business strategies.
- Secure, Compliant Operations: Meet evolving privacy laws, governance frameworks, and industry standards.
- Flexible Deployment Models: Support for cloud-native, hybrid, and on-premise infrastructures.
Key Market Trends We Solve For
- Most enterprises (80%+) are investing in AI for data harvesting.
- 70% of enterprise data still goes unused due to poor collection processes.
- Businesses demand instant, high-quality, analysis-ready data to power AI, decision-making, and competitive strategies.
Ready to Build Your Next-Generation Data Harvesting Pipeline?
Want to dive deeper into how we combined advanced connectors, knowledge graphs, entity recognition, and flexible rules engines to deliver real-world outcomes?
Read the full case study to explore our technical approach, the challenges we overcame, and the tangible results we helped our client achieve.
