The Industry Landscape
The Mandate for Intelligence Acquisition in the Digital Age
For information processing firms, the ability to rapidly analyze, synthesize and distribute high-volume, high-velocity data is central to their value proposition. Their customers now demand real-time insights, tailored sector coverage and nuanced interpretations across markets, languages and domains.
Traditional methods of tracking and processing information are too slow and labor-intensive. To stay competitive, leading firms are turning to Gen AI tools and intelligently automated workflows to power scalable insight engines, delivering faster turnaround, greater consistency and deeper strategic relevance.
The Client Challenge
Manual Processes. Slow Turnaround. Data Obsolescence. Limited Scalability.
The client relied on manual efforts to track and curate news and developments across the infrastructure sector. Analysts spent hours conducting open research, identifying, processing and updating relevant information on a proprietary database. As sector coverage widened and expectations for real-time updates grew, this model came under pressure.
To scale efficiently, the firm sought to embed intelligent technologies into its knowledge gathering operations. Specific objectives included:
The Solution
Gen AI-powered Research Engine
As a digital-led domain partner, WNS leveraged its customizable cognitive information processing tool, InfoTurf.ai, to automate the sourcing, extracting, processing and updating of industry-relevant details on the client database.
Key components of the solution included:
The Outcome
Accelerated, High-quality Intelligence Gathering
The engagement delivered a streamlined research process that drove measurable improvements in productivity, data capture quality and turnaround times. This enabled the client to accelerate and scale sector-specific coverage with greater breadth and depth, freeing analysts to focus on higher-value tasks.
Increase in coverage
increase in data fields populated, reflecting deeper coverage
wider coverage, strengthening the overall database
Building on the solution’s success, the client is exploring the feasibility of extending InfoTurf.ai across additional industries, expanding intelligent automation adoption across the enterprise.
FAQs
1. How does Generative AI improve intelligence gathering for rating agencies?
Generative AI improves intelligence gathering by automating the most time-consuming parts of research—such as sourcing, filtering, extracting, and structuring information from large volumes of unstructured data. For rating agencies, this means faster access to relevant sector developments without compromising accuracy. In this case study, Gen AI was combined with a human-in-the-loop model, ensuring that analysts retained control over judgment-based decisions while benefiting from AI-driven speed and scale.
2. Why is human oversight still important in Gen AI-powered research platforms?
Human oversight is critical because intelligence gathering is not just about collecting data—it’s about context, relevance, and credibility. While Gen AI can rapidly process and summarize information, expert analysts validate sources, assess materiality, and apply domain judgment. This hybrid approach reduces the risk of data bias or misinformation and ensures that insights remain reliable, auditable, and aligned with industry standards, especially in regulated environments like credit ratings.
3. What business outcomes can enterprises expect from AI-driven intelligence platforms?
Enterprises can expect faster turnaround times, broader coverage across sectors, and more consistent data quality from AI-driven intelligence platforms. More importantly, these platforms shift analyst effort away from manual data collection toward higher-value insight generation. In this case, the transformation enabled wider sector visibility, deeper data capture, and a scalable research model that supports future growth without linear increases in cost or headcount.
4. Why should enterprises choose WNS for Gen AI–powered intelligence transformation?
Enterprises choose WNS because it combines deep domain expertise with proven Gen AI platforms and governed delivery models. Rather than deploying standalone AI tools, WNS designs end-to-end intelligence workflows that integrate automation, analytics, and human expertise. This ensures faster insight generation, consistent data quality, and scalable operations aligned with business and regulatory needs.
5. How does WNS ensure accuracy and governance in Gen AI–driven research solutions?
WNS applies a human-in-the-loop operating model where domain experts validate, refine, and contextualize AI-generated outputs. This approach is supported by structured workflows, source traceability, and quality checks that reduce risk and improve trust. As a result, enterprises gain the speed of Gen AI without compromising on accuracy, explainability, or compliance.
6. Can WNS Gen AI intelligence solutions scale across industries and use cases?
Yes, WNS designs its Gen AI intelligence solutions to be modular and industry-agnostic. Platforms like InfoTurf.ai can be configured for different sectors, data sources, and research objectives, enabling enterprises to scale intelligence gathering across multiple industries. This flexibility allows organizations to extend AI-driven research capabilities without rebuilding systems or disrupting existing processes.