Success stories

Needl.ai Transforms Investment Firm's Research Workflow and Decision Making

Needl.ai halved the time an Indian boutique investment firm takes to write a research note, from about ten days to five, across more than 144 quick notes a year.

Asset Management26 Mar 20254 min read

144+Quick notes a year
8.7 / 10Analyst satisfaction

The customer is a prominent Indian boutique investment firm that focuses on direct investments in listed Indian equities. With close to US$1B AUM, analysts rely on a vast array of financial data sources to produce high-quality research reports and intelligence briefs.

What was the challenge?

The customer faced key operational inefficiencies in its research and intelligence processes, leading to increased workload, slower turnaround times, and inconsistent outputs.

Ineffective Research Workflows

Analysts spent excessive time manually filtering through news, reports and market data, leading to inefficiencies in report generation and delays in decision-making.

Excessive Noise

Existing news feeds contained a lot of irrelevant and generic market news, share price movements and trading volumes, making it difficult to extract relevant, valuable insights which were lost in the noise.

Lack of Customization and Control

Analysts wanted more flexibility in terms of report templates, keyword exclusions, and real-time refinement of AI-generated content.

Inefficient Learning Mechanisms

Their existing platform lacked an adaptive system that could learn from user feedback to improve content relevance and reduce manual adjustments.

How did Needl.ai help?

Needl.ai deployed its solution on the customer's cloud, following customer-defined milestones and custom optimizations, and integrated a broad set of financial data sources so analysts could move from raw information to decision-ready research quickly and securely.

Automated Information Extraction: Needl.ai parsed reports and key news alerts to extract relevant insights.

Intelligent Feed Curation: Filters reduced noise and prioritized relevant content.

Custom Report Generation: AI-generated reports were tailored to the customer's specific templates, often condensing 500+ pages of information into concise 20-page reports containing only relevant insights with references and citations to source document(s).

Learning-Based Adaptation: The filtration and prioritization of insights improved with user feedback and movements, thus reducing manual effort.

Conversational Interface: RAG-powered interface allowed analysts to query data seamlessly for quick insights and decisions through natural conversation.

What changed?

Within the first year of deployment, Needl.ai delivered measurable improvements for the customer:

✓

Increased Research Throughput: analysts produced 144+ quick note reports annually, with each note generated within 5 days instead of about 10 days, improving efficiency by 50%+.

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Increased Accuracy of Reports: complex AI-generated custom reports maintained a 95% to 100%+ accuracy rate, due to reduced noise and irrelevant financial data.

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High User Satisfaction: analysts reported an average satisfaction score of 8.7 on a scale of 10.

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Continuously improving research through an AI-driven learning mechanism.

“The ability to generate reliable, high-quality summaries and reports from extensive datasets allows us to focus on deeper analysis and quick decision-making to seize the right opportunities. The AI-driven learning mechanism ensures that our research is continuously improving, and Needl.ai has completely surpassed our initial expectations!”
Senior Analyst

Questions about this story

What slowed the firm's research?

Analysts filtered news, reports and market data by hand, and generic feeds buried the few items that mattered.

How does Needl.ai produce the reports?

It extracts insights from reports and news, filters out the noise and writes in the firm's own templates, often condensing 500+ pages into about 20, with citations to the source documents.

What changed?

Each quick note takes about five days instead of ten, analysts write more than 144 a year, and they rate the system 8.7 out of 10. See analyst note generation.

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