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Data and Model Engineering Services | iOPEX

AI Engineering

Data & Model Engineering
Services

Convert Data Silos to Long-term enterprise memory for Responsible AI solutions

Build an AI infrastructure to streamline data silos, fine-tune, test, manage, maintain, and govern smaller models that are cheaper to run along with mega models is the way forward for deploying enterprise-wide GenAI solutions.

Enterprise AI Levers: Organized Data and Custom Models

Harvest enterprise data & build reliable models to fuel AI adoption

Combining unified data with the power of AI models is an important phase in "Byte-Size" Total Digital Transformation journey to amplify the outcomes in enterprises. Data and Model Engineering is one of the key steps to build AI-embedded actions in business systems to enhance customer and employee experience. Enabling organizations to adeptly manage the nuances of integrating responsible AI, placing a high priority on security, compliance, and ethical development are imperatives.

Simplify
Trust
Compliance
Governance
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Ease of Use & Adoption
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Data Privacy
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Continuous Management
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Transparency & Trust

Make AI Regulatory for all : Simplifying AI Compliance & Navigating Regulations for enterprise wide adoption

Protecting Enterprise Data :Empowering Secure AI Adoption in Regulated business functions and domains

Continuous AI Oversight : Ensure Compliance with appropriate Guard Rails, Model Monitoring and Feedback

Comprehensive Reporting: Promoting Transparency and Trust with Comprehensive AI Reporting

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Assess your current state of data readiness?

Build 360° Digital Experience through Data & AI Models

AI driven Digital Excellence

Our proprietary AI Engine and framework "elevAIte" plays a crucial role in aggregating, curating, detecting and enforcing right datasets are fueled to the AI models. From the perspective of ensuring Responsible AI, we uncovers potential risks, compliance & privacy challenges relating to data and provide options to govern, mitigate, and remediate continuously use ML-Ops.

Scaling Enterprise Data For The Future 2

Building & Scaling Enterprise Data

Integrate, curate, & train your enterprise data into AI models, lay the foundation for building the infrastructure for AI.

Building Foundation Ai Models

Base Model Design & Deployment

Leverage best-of-bread foundation models / seamlessly integrate with the leading AI models like OpenAI etc., enabling the foundation for a strong enterprise-wide AI adoption.

Finetune Ai Models For Enterprises

Fine tuning with RLHF & Prompts

Adapt best-in-class foundation models / incorporate custom models with Reinforcement Learning from Human Feedback (RLHF) & Prompts. Continuously improve context & relevance for predictable outcomes.

Deploy Integration With Enterprise Apps

Deploy & Integrate with Enterprise Apps

Build and deploy next generation applications leveraging Gen-AI framework to dip into the power of your enterprise data source.

Knowledge Engineering

Build long-term enterprise memory

Unlock your data’s full potential to fuel AI by efficiently managing and refining organizational datasets.

  • Enable Enterprise AI by building a pipeline for raw data collection, curation, and preprocessing.
  • Refine data through annotation and evaluation using a business focused approach to maintain relevance and quality. 
  • Enrich the data with context augmentation, resulting in high-quality information that empowers strategic advantages. 
  • Integrate the high-quality datasets into the AI models to enhance their performance.
  • Feature Engineering - Apply the right embedding models on enterprise documents to provide the right context. 

Model Engineering

Fine-tune base models on proprietary data

Continuously fine-tune base models using enterprise data for enhanced performance. Streamline experiment comparisons across multiple LLMs, prompts, and strategies and effortlessly deploy the most promising variants for consumption.

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Private Long-Term Memory

  • Facilitate seamless access to diverse knowledge bases ensuring models have a broad information spectrum.
  • Integrate with leading enterprise connectors like Google Drive, Confluence, Slack, Microsoft SharePoint, and more.
  • Transform knowledge base data into powerful embedding, creating a reliable long-term memory accessible to your models.
  • Optimize model performance through continuous fine-tuning of enterprise data using AI workbench and prompt engineering. 
  • Empower your applications with efficient data retrieval, enhancing their capabilities for streamlined information access.
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Fine-Tuning

  • AI Workbench data engine empowers models through fine-tuning, ensuring optimized performance tailored to unique business needs.
  • Optimize the performance of the base model by leveraging the proprietary data enabling them to excel in handling high priority tasks with exceptional accuracy and efficiency.
  • Customize and refine base model to enterprise need for unlocking the true potential of AI delivering results that precisely align with specific requirements.
  • Provide customized solutions to meet the complexities of enterprise demands by recognizing the limitations of out-of-the-box, base foundation models.
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Reinforcement Learning from Human Feedback (RLHF)

  • AI Workbench Data Engine framework elevates model performance by customizing outputs to unique requirements. 
  • Evaluate and fine-tune model performance with diverse prompts, identifying weak points and incorporating enterprise-specific human preferences. 
  • Implemented continuous feedback-driven fine tuning process ensuring consistently superior accuracy and performance.
  • Rely on AI Workbench capabilities to consistently refine and optimize model outputs, aligning them perfectly with unique enterprise needs.
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Prompt Engineering

  • Enhance AI solutions with expert guidance personalized to address specific business challenges.
  • Ensure that the knowledge generated aligns seamlessly with brand and voice guidelines.  
  • Employ red teaming including prompt injection techniques to identify vulnerabilities and fortify the system’s resilience proactively.

Customer Proof Points

Popular Uses cases deployed

Telecom

Improving network service management, enhance customer services via case summarization and agent assistances.

Hi-Tech

Improving Mean Time to Resolve (MTTR) and predictability for Technical support and Technology operations through K'base optimization and utilization

Retail/Media

Personalizing brand-based content and campaign experiences and increase sales based on past performance and creative insights

Healthcare

Enhancing patient outcomes and streamlining operations by converting data to best step actions and feed operators

Manufacturing

Optimize production processes and improve compliance & quality control via information summarization and smart searches

Talk to an expert

Develop Custom Models to fast-track GenAI adoption

Business Outcomes

Generate continuous value

Enhanced Model Accuracy

Customized and fine-tuned models lead to improved accuracy, reducing errors and ensuring more reliable AI-driven solutions.

Competitive Advantage

Tailored models and prompt engineering can give your organization a competitive edge by offering more effective and responsive AI solutions, setting you apart from competitors.

Scalability

Well-engineered models and prompt-driven interactions are scalable, allowing businesses to handle growing volumes of data and user interactions without sacrificing performance or quality.

Improved User Experience

Customized AI interactions and user-centric prompt engineering lead to better user experiences, higher engagement, and increased user satisfaction, all of which can positively impact customer loyalty.

Operational Efficiency

Streamline operations by optimizing data retrieval processes, reducing manual intervention, and improving overall efficiency to free up resources and reduce overhead.

Cost Savings

Optimized models and AI systems are more efficient, requiring fewer resources and reducing operational costs.

What We Think?

Our Perspective

001 Wwt

Data with AI-ML Approach | Key Drivers of Enterprise Transformation

Explore the significance of data as a valuable asset and how it transforms enterprises to be more data-driven, unlocking their untapped potential for growth and success.
002 Wwt

Data Analysis & Visualization | Simplifying Data Exploration in Enterprises

Unlock the power of data analysis and visualization and discover how it promotes creative data exploration, transforms decision-making, elevates customer understanding, and promotes success.
003 Wwt

APA | Democratizing Data Enabling Workforce Empowerment

Discover the latest in Analytic Process Automation (APA) and how it empowers your workforce and propels businesses toward a data-driven era of success.
004 Wwt

Cognitive Automation with AI-ML | Driving Enterprise-wide Level Automation

Get insights on how we build cognitive automation, empowering clients to seamlessly integrate advanced tech into the digital fabric and redefine the future of automation.
005 Wwt

AI and ML | Navigating Future-Ready Operations

Explore the convergence of AI and ML, & how it elevates enterprise security, enriches user experience, and reshapes the future with intelligent automation.
006 Wwt

Data Empowerment | Strategic Principles Driving Automation Excellence

This whitepaper discusses the essential guiding principles driving digital automation using the CoE approach and enabling enterprises toward automation excellence and transformative success.
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Build a strong Data & AI Model Mastery

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