Document Processing
Tata Projects had to review 1,000-2,000 page tender packages with non-standard terms, scanned tables, and frequent corrigenda, so manual analysis took more than four days per bid and made it difficult to spot risk and respond quickly enough to stay competitive.
Reported impact
TenderSummAIze gave Tata Projects a faster and more reliable bid-preparation workflow, reducing manual review time, increasing accuracy, and helping the company evaluate more tenders with the same teams while shifting effort from clerical document handling to strategic commercial analysis.
Tata Projects and TCS built TenderSummAIze, a generative AI tender-management portal on Microsoft Azure that turns bulky infrastructure bid documents into structured, searchable working material for legal and contracts teams. Tender files and scanned pages are processed with Document Intelligence and Microsoft Azure OpenAI so the system can chunk clauses semantically, map corrigenda back to the original document set, answer tender questions, and generate tailored summaries. Microsoft Azure Durable Functions orchestrates the long-running workflow, while Cosmos DB and Microsoft Azure Queue hold state and scale data movement across the pipeline. The portal lets teams upload, review, query, summarize, and track tenders through one interface, replacing reactive document reading with a governed AI workflow that surfaces liabilities and key terms in time for faster bid decisions.
Tender documents, scanned pages, and corrigenda are uploaded into TenderSummAIze, where Document Intelligence extracts content and Microsoft Azure OpenAI organizes clauses, highlights liabilities, answers questions, and produces summaries. Durable Functions and Azure Queue orchestrate the long-running steps, Cosmos DB maintains the working state and document lineage, and legal and contracts teams consume the results through the portal for faster bid decisions.
"Over 20% improvement in bid handling capacity thus impacting competitiveness"
"Over 50% reduction in manual effort: Processing time reduced from four days to less than two days"
"Over 60% improvement in document accuracy"
"Processes over 250 pages of tender documents in under 25 minutes"
"The solution leverages a robust tech stack, including Microsoft Azure OpenAI and Document Intelligence, for advanced natural language processing, Microsoft Azure Durable Functions for reliable long-running tasks, Cosmos DB and Microsoft Azure Queue for scalable data management"
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
The official registered office page lists “Corporate Centre, 3rd Floor, Building Block B, 34 Sant Tukaram Road, Carnac Bunder, Mumbai 400009”.
Related
Google Cloud Sample Archived · Oct 9, 2026 CBRE As the world's largest commercial real estate services and investment firm, CBRE delivers a fully integrated suite of financial, property accounting, and fund administration services. Managing asset-level transactional… CBRE is leveraging the Gemini platform with the help of McKinsey to rapidly build, deploy, and scale… Agent Development Kit (ADK) · Gemini platform 
TCS Sample May 10, 2026 Astro Astro needed faster and more consistent metadata generation across its web and mobile platforms, but manual tagging slowed content operations, limited scale, created classification inconsistencies, and reduced the… 20% improvement in customer satisfaction Amazon Bedrock · NOVA multimodal model · TCS AI VX Studio 
NVIDIA Sample Feb 2, 2026 Worley Worley needed to unlock more than 50 years of engineering knowledge across over 100,000 documents, but fragmented tools, isolated repositories, and slow document retrieval caused engineers to waste time and made it hard… 100,000+ documents Microsoft Azure · Milvus · NVIDIA AI Enterprise 