Generative AI Development Service.

Shaping India's AI Frontier.

About Us

Edubild is a leader in enterprise AI, specializing in innovative generative AI solutions, custom LLM development, and deployment of autonomous agents to tackle critical business and governance challenges. Our expertise has been recognized by prestigious clients—including MOSPI—for intelligent document search and legacy data automation projects.

From quick AI prototypes to enterprise-grade production systems, Edubild helps organizations unleash the true potential of their data, accelerate decision-making, and future-proof their processes.

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Our Services

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RAG Intelligent Search

Empower your business with advanced AI search that actually understands context. RAG-based systems combine the power of Large Language Models (LLMs) with real-time data retrieval, enabling highly accurate, context-aware search across your knowledge base, documents, or support data in multiple languages and domains.

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Legacy Data Extraction & OCR

Digitize, extract, and utilize data from legacy systems and documents. We use advanced OCR and NLP techniques to extract structured data from scanned documents, handwritten forms, printed reports, and legacy systems. Unlock valuable insights from historical data by converting it into actionable digital formats.

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LLM Business Integration

Bring AI power into your existing software, ERP systems, and web portals. We integrate advanced generative AI (LLMs) directly into your current platforms whether it's a custom ERP, CRM, HRMS, or web portal. Our solutions enable features like smart search, document automation, chatbots, and intelligent analytics without replacing your existing systems.

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AI Agents

Deploy self-learning autonomous AI agents that streamline your operations. We build intelligent agents that independently adapt to your workflows, reducing manual effort and increasing operational efficiency. From customer service automation to intelligent backend processes, our AI agents optimize daily tasks and enable smarter business decisions.

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AI Model Fine-Tuning Services

Custom-trained AI models tailored to your domain and data. Off-the-shelf models aren’t always enough. We fine-tune open-source and proprietary LLMs on your specific datasets to improve performance, accuracy, and contextual understanding delivering models that truly understand your business language and needs.

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Open Source ERP Development

We specialize in developing and customizing open-source ERP systems like ERPNext, Odoo, and more tailored to fit your business processes. Whether you're a startup or an enterprise, our solutions offer flexibility, cost savings, and full ownership without vendor lock-in. From deployment to module customization and third-party integrations, we handle everything end-to-end.

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Frappe Development

We provide complete development, implementation, and customization services across the Frappe Framework and its entire ecosystem. Our services cover a wide range of Frappe modules, including ERPNext, Desk, HRMS, Learning, CRM, Helpdesk, Lending, Books, Cloud, and School. We deliver tailored Frappe solutions from custom apps to full deployments that scale with your business.

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Custom Software Development

We design and develop custom software solutions tailored to your unique business needs. Whether you require a standalone application, business automation tool, or a fully integrated system, our team builds scalable, secure, and user-friendly software from the ground up. From idea to deployment — we handle planning, design, development, testing, and ongoing support to ensure your solution delivers real value and performance.

LLMs and AI models we use

Technology Stack

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Generative AI:
Applications Across Key Indian Industries

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FinTech

  • Enhance Customer Experience: Provide AI-driven personalized financial advice and automated customer service.
  • Leverage Enterprise Knowledge: Utilize AI to analyze large volumes of financial data for better investment and risk management decisions.
  • Optimize Processes: Automate fraud detection and claims processing using AI algorithms.
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EdTech

  • Enhance Customer Experience: Develop AI-driven personalized learning experiences and adaptive testing.
  • Leverage Enterprise Knowledge: Analyze student data to tailor educational content and identify learning gaps.
  • Optimize Processes: Streamline course design and grading systems through AI automation.
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Healthcare

  • Enhance Customer Experience: Use AI to offer personalized treatment plans and virtual health assistance.
  • Leverage Enterprise Knowledge: Implement AI for predictive diagnostics and patient data analysis.
  • Optimize Processes: Automate administrative tasks like patient scheduling and medical record keeping.
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Manufacturing

  • Enhance Customer Experience: Custom manufacture products based on AI analysis of customer preferences.
  • Leverage Enterprise Knowledge: Use AI for predictive maintenance and quality control.
  • Optimize Processes: Automate production lines and optimize supply chain management.
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Retail and eCommerce

  • Enhance Customer Experience: Personalize shopping experiences with AI-powered recommendation systems.
  • Leverage Enterprise Knowledge: Analyze customer behavior data to optimize marketing strategies.
  • Optimize Processes: Improve inventory management and logistics with predictive AI models.
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Telecom

  • Enhance Customer Experience: Enhance customer service with AI-driven support systems and personalized offers.
  • Leverage Enterprise Knowledge: Use AI to manage and analyze network traffic data for improved service quality.
  • Optimize Processes: Automate network operations and maintenance tasks.

Our Trusted Development Process

1
Consulting Phase

Objective: To understand client-specific needs and the potential of LLMs to meet those needs.

Initial Client Meeting: Engage with the client to explore and define potential use-cases relevant to their business.

Evaluation: Assess the client's existing content and data infrastructure to identify opportunities for LLM enhancement.

2
Identifying Scope

Objective: To define and confirm the feasibility of the LLM solution for the client’s issues.

Data & Content Assessment: Review the client’s data types and volumes to ensure alignment with LLM capabilities.

Problem Definition: Clearly define the client's objectives and expectations from the LLM deployment.

Approach Selection: Choose the most suitable LLM frameworks and tools based on the client’s needs.

Ethical & Bias Evaluation: Assess and plan for any potential biases or ethical concerns related to LLM use.

3
MVP (Minimum Viable Product)

Objective: To implement and validate the effectiveness of a basic LLM solution.

Setup: Integrate the LLM into the client’s environment using appropriate platforms or APIs.

Prototype Development: Develop a simplified version of the solution tailored to the defined use-case.

Initial Testing: Conduct tests to evaluate the accuracy, relevance, and reliability of the LLM outputs.

Feedback Collection: Gather and analyze feedback from end-users or stakeholders to gauge the solution’s impact.

4
End-to-end Development

Objective: To develop a full-scale, comprehensive LLM solution.

Fine-Tuning: If permitted, optimize the LLM with specific data sets to enhance performance.

Integration: Seamlessly incorporate the LLM into the client’s existing digital ecosystems.

UI/UX Development: Design user interfaces that enhance interaction with the LLM, ensuring a positive user experience.

Comprehensive Testing: Perform extensive testing to identify and correct any issues, focusing on output accuracy and potential biases.

5
Scaling

Objective: To expand the LLM’s application scope and user base.

Infrastructure Enhancement: Upgrade infrastructure to support increased data and query volumes.

Parallel Processing: Implement methods to manage multiple simultaneous LLM requests efficiently.

Deployment Strategies: Determine optimal deployment solutions (cloud vs. on-premises) based on scalability needs and client preferences.

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Maintenance

Objective: To provide continuous support and updates for the LLM solution.

Continuous Monitoring: Regularly monitor the system to ensure optimal performance.

Regular Updates: Implement necessary updates and adjustments to the LLM based on new technology developments and client feedback.

User Feedback Loop: Establish a continuous feedback mechanism to improve and adapt the LLM solution over time.


Blogs

Tech

Artificial Intelligence in Business Growth

Artificial Intelligence (AI) is revolutionizing the business landscape, transforming how companies operate, make decisions, and engage with customers. From startups to established giants, businesses o...

Saksham Gupta
Saksham Gupta

26-08-2024

Tech

Unlocking Your Organization’s Generative AI Potent...

Generative AI is no longer just a buzzword—it’s a game-changer that’s revolutionizing how businesses create content, engage with customers, and innovate products and services. This b...

Saksham Gupta
Saksham Gupta

23-08-2024

Tech

Google vs. OpenAI: The Pricing War That Could Chan...

The ongoing battle for lower prices between Google and OpenAI is indicative of the broader struggle for supremacy in the AI and cloud services market. As these companies compete fiercely to dominate t...

Saksham Gupta
Saksham Gupta

23-08-2024

More Blogs

Frequently asked questions

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Phone: +91-9829566876

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