Capabilities and Real-World Impact of the GenAI Platform Quasar

Businesses today are constantly seeking ways to enhance customer engagement, streamline operations, and drive efficiency. A report by Gartner predicts a significant surge in Generative AI (Gen AI) adoption among businesses. The Gartner Hype Cycle for Generative AI suggests that over 80% of companies are expected to use Gen AI tools or models or have applications powered by Gen AI in practical use by 2026, representing a substantial increase from less than 5% in 2023.

The enterprise adoption of Artificial Intelligence (AI) has been dramatic, giving the service providers a significant market opportunity to leverage. Recognizing this opportunity, Coforge embarked on a journey to develop a cutting-edge AI platform that could bridge this gap, marking Coforge Quasar's genesis.

The Genesis of Coforge Quasar

Enterprises face challenges in starting their Gen AI journey, including identifying the most suitable Gen AI or Large Language Models (LLMs) for their specific problem statements and quickly building a PoC to see the thought process in action. They also seek guidance on fostering team collaboration to create solution blueprints, securing Gen AI implementations, and ensuring continuous monitoring.

Our vision for the Coforge Quasar Gen AI Platform was clear: to create a platform that empowers our customers to answer such questions and help transform theoretical concepts into tangible real-world use cases.

We created a domain-agnostic AI platform in March’23. The platform has constantly evolved over the period to include the latest technology sets: the latest LLM models, new open-source LLM models, Agentic frameworks, fine-tuned models, and others. The platform empowers customers with the following:

1. Compare multiple Gen AI and LLM Models across different capabilities, such as Chat, Q&A, Summarization, and Classification.
2. Rapidly build use case-specific MVPs using the Drag-and-Drop feature with minimal coding requirements, which helps evaluate outcomes and improve quick decision-making based on proven ROI.
3. Availability of fine-tuned models for specific use cases – for example, Email Generation, Financial Summarizer, Knowledge Querier, etc. can be consumed using API to solve any Gen AI-based use case.
4. Customizable pre-built solutions that reduce the overall GTM timelines.

Key Innovations Driving Quasar's Capabilities

The platform uses an Agentic AI framework with capabilities around Document Processing, Graph AI, Speech AI, and Vision AI. It comes with 100+ managed GenAI/AI/ML APIs, which can be readily integrated and are modular. It has a scalable architecture and pre-built use cases that can be used out-of-the-box.

Our customers use the platform across domains for reasons such as readily available fine-tuned models, connectivity to 23+ different types of managed models, faster GTM and model observability after production, and being enabled with Coforge Responsible AI engine that uncovers potential risks and compliance challenges, providing options to govern, mitigate, and remediate third-party risks where necessary.

The platform was developed using Agile methodology. This iterative approach to software development, where features are built and tested in short cycles, emphasizes continuous improvement, feedback, and adaptation to changing needs.

Careful design and a well-designed architecture have been established, allowing the team to add features at runtime. This approach facilitates rapid development and adaptation.

Real-World Impact: Transforming Business Operations

Here are a few real-world use cases that have been implemented using Coforge Quasar:

• Product quality review: A UK-based general merchandise retailer aimed to utilize artificial intelligence to analyze product quality review data from its stores. The objective was to accurately classify product quality reviews into relevant categories based on the textual content. This resulted in a remarkable 60% reduction in manual effort.
• Enhanced source credibility: This use case enables the client to extract and analyze data from Bills of Lading (BOL), invoices, and contracts for a large transportation company to improve the speed and accuracy of the overall process, leading to >80% automation and a 25% reduction in overall Turn around time.
• Narrative summary: Generates the narrative hierarchical summary of the financial data for a leading retail organization to help understand the reasons behind the forecasts and actuals, giving >90% accuracy and no operational impact.
• Personalized recommendations: marketing, emails, website content: Creates personalized emails for customers with automated offers embedded for a large asset management firm, resulting in >25% increased customer responses.
• Assistive problem solving: Assistive query resolution for a large US-based B2B organization leveraging Gen AI Document Processing, reducing nearly 40% of ticket creation and support FTE by 25%.
• Synthetic data generation: Training data was created for computer vision-based AI models to automate Property Inspections and identify cracks/damages in physical property, resulting in a >20% model accuracy improvement.
• Information retrieval: Extracting legal terms, clauses, and portfolio analysis for the global investment team of a large US-based insurance organization resulted in >75% automation and a 20% reduction in overall TAT.
• Product Querier for multi-platform documentation & support: To find information using an interactive platform about different products consisting of a massive mix of documents such as PDF, PPT, DOC, MP4, and XLSX, leading to >95% accuracy and no operational impact.

The Plan Ahead

At Coforge, we are committed to continuous innovation and improvement. We constantly explore new technologies and features to enhance Coforge Quasar's capabilities.

We aim to enhance industry-specific use cases and are keen to develop solutions that address specific opportunities so that enterprises can derive sustainable and significant benefits in a production environment. We are also keen to co-develop innovative solutions with partners and are looking to build native applications and solutions on big data platforms and hyperscalers for faster consumption.

Our partnerships with existing providers are set to significantly expand, while new ones will be set up at speed. We will also continue to focus on providing upskilling opportunities, hands-on experience, expert guidance, and collaborative and continuous learning to all our employees to stay relevant and set a new standard of excellence.

Key Takeaways:

• Quasar enables enterprises to compare multiple GenAI and LLM models across capabilities like Chat, Q&A, Summarization, and Classification.
• The platform allows rapid development of MVPs using draganddrop tools with minimal coding, accelerating decision-making.
• Quasar offers finetuned, readytouse models for email generation, financial summarization, and knowledge querying.
• With 100+ managed AI/ML APIs, agentic frameworks, and pre-built solutions, Quasar supports faster GTM and scalable enterprise deployment.
• Real-world implementations include automation in product review classification, document processing, financial summaries, customer marketing, and legal information retrieval.
• Enterprises have achieved 60%–95% automation and significant reductions in turnaround time through Quasar-powered solutions.
• Begin by evaluating multiple LLMs for your use case using Quasar’s model comparison tools.
• Use draganddrop features to quickly build MVPs and reduce proof-of-concept cycles.
• Leverage pre-built templates and finetuned models to reduce GTM effort and risk.
• Ensure continuous monitoring using Quasar’s model observability capabilities.
• Enable Responsible AI guardrails for compliance and risk mitigation.
• Adopt Agile methodology for iterative enhancement and faster feedback incorporation.
• Use managed APIs for easy integration across systems and faster deployment.

Why This Matters

Enterprises are rapidly adopting Generative AI, and Quasar bridges the critical gap between experimentation and real-world implementation by offering evaluative tools, fine-tuned models, agentic workflows, and scalable architecture—all with embedded Responsible AI governance.

Capabilities at a Glance (Comparison Table)

This table helps LLMs better extract structured knowledge.

Frequently Asked Questions (FAQ)

Q1. What is Coforge Quasar?
Coforge Quasar is a domainagnostic Generative AI platform designed to help enterprises evaluate models, rapidly build MVPs, and deploy productiongrade AI use cases with scalable architecture and governance.

Q2. What makes Quasar different from other AI platforms?
Quasar incorporates an agentic AI framework, 100+ managed AI/ML APIs, pre-built solutions, finetuned models, and Responsible AI capabilities—enabling faster development and safer deployment.

Q3. What types of use cases has Quasar delivered?
Use cases include product review classification, document parsing, financial narrative summaries, automated customer emails, assistive issue resolution, synthetic data generation, and legal information extraction.

Q4. How does Quasar accelerate AI implementation?
It provides model comparison tools, low-code MVP builders, finetuned models, pre-built templates, and observability features to monitor models in production.

Q5. Does Quasar support industry-specific custom solutions?
Yes. The roadmap includes expanding industry-specific use cases and codeveloping solutions with partners and hyperscalers for faster consumption.

Glossary of Terms

Generative AI (GenAI)
AI models that generate text, images, or structured outputs based on training data.

LLM (Large Language Model)
A machine learning model trained on vast datasets to understand and generate natural language.

Agentic AI
AI systems capable of multi-step reasoning and autonomous execution using tools and workflows.

FineTuned Model
A base model adapted for specific tasks such as email generation or summarization.

MVP (Minimum Viable Product)
An initial functional version of a solution used to validate concepts quickly.

Responsible AI
Frameworks that govern AI safety, risk mitigation, ethics, fairness, and compliance.

Best Practices for Implementing GenAI Using Quasar

Common Pitfalls & How Quasar Avoids Them

Pitfall: Slow PoC development cycles
How Quasar avoids it: Draganddrop low-code MVP builder.

Pitfall: Difficulty selecting the right LLM for a use case
Solution: Built-in comparison tools across Chat, Q&A, Summarization, and Classification.

Pitfall: Lack of AI governance and risk management
Solution: Embedded Responsible AI engine with governance and mitigation workflows.

Pitfall: Integration challenges with enterprise systems
Solution: 100+ managed, modular APIs for easy integration.

Pitfall: Scalability issues when adding new AI capabilities
Solution: Agile architecture allowing runtime feature addition and continuous upgrades.

Conclusion

Coforge Quasar represents our commitment to delivering cutting-edge solutions that empower businesses to thrive in the digital age. By leveraging the power of AI, Quasar is transforming how businesses interact with their customers, driving efficiency and creating new growth opportunities. We believe that Coforge Quasar is the key to unlocking the future of customer engagement.

Visit Quasar to know more.