WHAT WE OFFER
Generative AI Development Services
We help organizations adopt Generative AI responsibly, ensuring fairness, transparency, and accountability across the entire AI lifecycle. Our team builds governance frameworks, bias detection protocols, and compliance strategies that align with global standards.
Healthcare
Transformed Medical Research with a Generative AI Chatbot
Markovate engineered a Conversational AI system that leverages advanced LLMs to deliver medically verified information to breast cancer patients. By integrating real-time research data and clinical trial repositories, the chatbot provides reliable, context-aware guidance while maintaining strict compliance with healthcare data standards.
- Reduced query response time by 60%
- Evidence-based responses supported by trusted data sources
- Summarizes lengthy and complex content into clear, actionable insights
- Streamlined information retrieval, improving decision-making
Real Estate
Reduced Inspection Costs and Time by over 28% for Property Inspectors
We harnessed Generative AI to analyze thousands of NVMS property images, automatically detecting visual anomalies with precision. Alongside, we built a Conversational AI chatbot that streamlines customer interactions and improves service efficiency.
- Deep learning and computer vision driven image data extraction
- GPT-based NLP chatbot for enhanced customer experience
- Improved work efficiency by 80%
- Image classification for detecting anomalies
Insurance
Redefined Large-Scale Document Processing for Accurate Insurance Submissions
We developed an Generative AI-powered document data extraction tool that automates data collection and validation for insurance brokers and underwriters, ensuring accurate submissions and enabling faster and more precise underwriting decisions.
- 80% improved accuracy in data extraction and validation
- Identifies missing fields and ensures data consistency
- Scalable for handling high-volume submissions
- Improved underwriting decisions with accurate data insights
Legal
Reimagine Legal Support Driven by in-Depth Legal Research
Our team leveraged Generative AI to fasten legal document analysis and drafting for a medium-sized law firm in Chicago.
- Legal Chatbot Assistant
- Improved Communication Efficiency
- Research Time Reduction by 64%
Manufacturing
Revolutionized ERP System with an AI Agent for Streamlined Order Management
Markovate engineered an ERP AI agent for a major U.S. manufacturer that automates customer order management and inventory workflows, significantly improving order accuracy, real-time visibility, and fulfillment efficiency.
- Automated order placement and real-time tracking
- 95% order accuracy with reduced response times
- Seamless ERP integration for inventory and pricing updates
- Enhanced operational productivity across departments
WHY US
How do we build a Generative AI solution for businesses?
Markovate leverages advanced algorithms and data-driven insights to deliver unparalleled accuracy and relevance. With a keen focus on data security, model architecture, model evaluation, data quality and MLOps management, we can develop highly competitive Generative AI applications for our clients.
We streamline data preparation for businesses, employing advanced techniques to enhance data quality. Our AI engineers collaborate closely with client teams to eliminate noise and inconsistencies, ensuring your data is ready for effective use.
We recognize that data security is as important as the generative AI solutions themselves. Therefore, our AI engineers employ multi-factor authentication and robust encryption techniques to protect our clients’ data. With encryption protocols for data transmission and AES for data retrieval, we ensure seamless and secure handling of client data.
To ensure that the generative AI solutions meet your business needs, we employ rigorous evaluation methods. The techniques we use help us to test the model’s effectiveness across different data subsets, focusing on key performance metrics such as accuracy and precision. We also fine-tune model to ensure optimal performance tailored to your specific requirements.
Our MLOps team specializes in deploying solutions, ensuring the validation of outputs, and effectively reducing data processing costs. They employ a range of tools to continuously conduct cost-impact analyses, helping to optimize the financial efficiency of the solution. Additionally, they focus on maintaining consistent performance, reliability and scalability across different environments.
We help in optimizing large language models to maintain high-quality outputs while managing computational costs. Using techniques like quantization and pruning, we ensure efficient scalability to meet growing demands of the business, all while keeping expenses in check to maximize the ROI.
PROCESS
What is our process for building Generative AI solutions
Data Analysis & Preparation
Before we begin the model development process, we help you with data analysis, cleaning, organizing, preparation and turn it into a format that is suitable for custom Generative AI solutions. This may include normalizing or standardizing numerical data, encoding categorical data, and possibly generating new features through various transformations to enhance model performance.
Data Pipeline
After gathering diverse and relevant datasets for training the generative AI model, we want to ensure data quality and relevance. Our team pre-processes the data and transforms it using data engineering techniques like normalization, feature engineering, and imputation to minimize the data maintenance cost. We then enhance the dataset and implement data versioning to track changes and ensure reproducibility—key aspects of our generative AI development services.
Experimentation
Based on the project requirements and objectives, we choose the appropriate architecture model and neural networks such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), or Transformer models. Once we select the Gen AI model, we work on model training and fine-tuning using the preprocessed quality data and evaluate it on performance metrics such as accuracy and relevance. The process we follow with our generative AI development services ensures that the selected model aligns with the project’s goals and delivers high-quality AI POC.
Data Evaluation
We rigorously evaluate the quality and relevance of the processed data to confirm its suitability for training. Leveraging advanced data evaluation tools like Guardrails, MLflow, and Langsmith, we conduct thorough assessment and validation processes. Additionally, we implement RAG techniques designed to detect and mitigate hallucinations within the generated outputs. We ensure that the Generative AI model maintains high levels of groundedness and fidelity to the training data, minimizing the risk of producing inaccurate or misleading results.
Deployment
Once we have a trained model ready and any necessary dependencies into a deployable format, we deploy it to the production environment using platforms like TensorFlow, AWS SageMaker, or AzureML. Finally, we implement a monitoring system to track the model performance in production. After the generative AI solution integration, we gather the user feedback and through the feedback loop, we improve the model over time.
Prompt Engineering
Our team defines clear and concise prompts or input specifications for generating desired outputs from the generative AI model. We experiment with different prompt formats and styles to optimize model performance and output quality. And eventually integrate prompts seamlessly into the user interface or application workflow, providing users with intuitive controls and feedback mechanisms.
Data Preparation
Before we begin the Generative AI model development process, we help organizations with data analysis, cleaning, organizing, preparation and turn it into a format that is suitable for custom Generative AI solutions. This may include normalizing or standardizing numerical data, encoding categorical data, and possibly generating new features through various transformations to enhance model performance.
Data Pipeline
After gathering diverse and relevant datasets for training the generative AI model, we want to ensure data quality and relevance. Our team pre-processes the data and transforms it using data engineering techniques like normalization, feature engineering, and imputation to minimize the data maintenance cost. We then enhance the dataset and implement data versioning to track changes and ensure reproducibility—key aspects of our generative AI development services.
Experimentation
Based on the project requirements and objectives, we choose the appropriate architecture model and neural networks such as Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), or Transformer models. Once we select the Gen AI model, we work on model training and fine-tuning using the preprocessed quality data and evaluate it on performance metrics such as accuracy and relevance. The process we follow with our generative AI development services ensures that the selected model aligns with the project’s goals and delivers high-quality AI POC.
Data Evaluation
We rigorously evaluate the quality and relevance of the processed data to confirm its suitability for training. Leveraging advanced data evaluation tools like Guardrails, MLflow, and Langsmith, we conduct thorough assessment and validation processes. Additionally, we implement RAG techniques designed to detect and mitigate hallucinations within the generated outputs. We ensure that the Generative AI model maintains high levels of groundedness and fidelity to the training data, minimizing the risk of producing inaccurate or misleading results.
Deployment
Once we have a trained model ready and any necessary dependencies into a deployable format, we deploy it to the production environment using platforms like TensorFlow, AWS SageMaker, or AzureML. Finally, we implement a monitoring system to track the model performance in production. After the generative AI solution integration, we gather the user feedback and through the feedback loop, we improve the model over time.
Prompt Engineering
Our team defines clear and concise prompts or input specifications for generating desired outputs from the generative AI model. We experiment with different prompt formats and styles to optimize model performance and output quality. And eventually integrate prompts seamlessly into the user interface or application workflow, providing users with intuitive controls and feedback mechanisms.
INDUSTRIES
Developing effective Generative AI solutions for every industry
Healthcare AI Solutions
We specialize in crafting tailored AI solutions for healthcare organizations aiming to adopt or enhance AI capabilities. Our expert team develops impactful integrations to advance diagnostics and streamline operations, ensuring each solution meets unique client needs.
Retail AI Solutions
Our AI expertise enables retail businesses to enhance customer experience and optimize inventory management. We develop personalized solutions that improve sales forecasting, customer engagement, and supply chain efficiencies.
Fintech AI Solutions
We deliver bespoke AI solutions to fintech firms seeking innovation in fraud detection, risk assessment, and automated customer service. Our tailored integrations enhance transaction security and operational efficiency, meeting specific industry needs.
SaaS AI Solutions
For SaaS companies, we provide AI-driven enhancements that improve user engagement, automate processes, and boost analytics capabilities. Our custom solutions are designed to integrate seamlessly with existing platforms, enhancing functionality and user experience.
Travel AI Solutions
We create customized AI applications for the travel industry to streamline booking processes, personalize customer experiences, and optimize operational logistics. Our solutions help travel businesses adapt to market changes and enhance traveler satisfaction.
Fitness AI Solutions
We build AI solutions for the fitness industry that personalize workout plans, track performance, and enhance user engagement through interactive applications. Our tailored approaches help fitness providers elevate their service offerings and client results.
Insurance AI Solutions
We help insurers harness AI to streamline claims, enhance customer experiences, and boost fraud detection. Our team builds customized solutions to address key insurance challenges, from underwriting and risk management to predictive analytics and claims automation.
Manufacturing AI Solutions
Our team collaborates with data-driven manufacturers to implement AI solutions at every level of their operations, from predictive maintenance and quality assurance to automated price forecasting and supply chain optimization.
TESTIMONIALS
What our clients say
See how businesses are using our AI solutions to make better decisions with measurable impact.
Within 3 months of working with Markovate, we reduced manual clinical coding work by 65%. We’re pleased with the AI agents supporting our workflows.
David V.
CEO, CodmanAI
Markovate’s AI platform helped improve our property inspection accuracy and reduce operational costs by 86%, helping us deliver a better customer experience.
Chris Cook
CEO, NVMS
Markovate’s AI Blueprint Classifier can process more than 150 drawings in a single pass, helping us prepare takeoffs and estimates faster.
Andrew B.
CEO, CivilTakeoff
Markovate helped us automate 95% of our paratransit workflows. We’ve been impressed by their team and the effectiveness of their solution.
Garrett Vandendries
Director & PMO, Trapeze
We worked with Markovate to build a financial tool for our business and clientele. The experience and results have exceeded our expectations. Markovate's team is great to have on your side if you need an experienced technology partner.
Michael Sedigh
CFO, 3M Corporation
As a retail business, finding the right technology partner was crucial. We partnered with Markovate, who expertly guided our product development from concept to launch. Their recommended innovative solutions have significantly enhanced our operations and reduced our costs.
John D
CEO, Aisle 24
Markovate’s legal AI assistant has reduced our argument preparation time by 78%. It supports our research and is used daily by our legal team.
Tate Lounsbery
Owner, Lounsbery Law Office, PC
Markovate built an AI workflow for investor presentations. With minor edits, we can now prepare presentations in 3 hours instead of several days.
Jacob A
Senior Associate, Madison Capital Group
Markovate’s AI solution helps us find information across support mailboxes and SharePoint, update FAQs, and maintain consistent customer responses. Within a few months, our overall work efficiency increased by 69%.
Tom
Partner, Very Mulberry
Markovate's AI Blueprint Classifier helped us significantly accelerate our quotations, cost estimations, and timeline planning. The automation and accuracy it brought to our blueprint analysis have been a major value-add to our pre-production process.
Jason Porter
COO, MPP Innovation
The AI Interview Agent has improved our hiring efficiency by 80% through natural conversations and automated scoring. Candidates can complete interviews anytime, giving our team greater screening flexibility.
Natalie C.
Talent Lead, AltaSpark
AltaSpark
DeVoice helps us manage customer support workflows and answer customer queries. Since implementation, we’ve seen a 54% increase in positive reviews.
Doughlus
CEO, Nebula Pie & Pizza
Nebula Pie & Pizza
For our live interviewing platform, we have worked with Markovate on building the infrastructure and roadmap planning. They have advised us on great solutions, and we highly recommend their team.
David Singh
VP Strategy and Operations, Kira Talent
We worked with both Rajeev and Mansi on Hawaii Revealed app development and launch. Excellent people with a thorough understanding of their business. They are experts in providing AI solutions for scalability and product modernization.
George Thompson
Sr. VP, Hawaii Revealed
I would recommend Markovate to businesses looking for a reliable technology partner. Their team combines strong technical skills with a deep understanding of business needs.
Lucie Lalumiere
President & CEO, Interactive Ontario
TOOL & TECHNOLOGY
Generative AI development Tech stack we use
Our experts recommend the best technology stack for custom Generative AI development to create cutting-edge solutions.
Leading brands we’ve worked with
Markovate helps ambitious companies turn AI into a competitive edge - making operations faster, smarter, and more resilient. Explore what this could mean for your business.
Discover how we can supercharge your business with AI. Our commitment to delivering tangible results has helped countless companies like yours achieve their goals. See the transformative impact of our AI, Generative AI solutions and imagine the possibilities for your business.
AI-MODELS
Rich expertise across diverse AI models
GPT-5
OpenAI’s most advanced model, delivering state-of-the-art reasoning, coding, and language generation.
Claude 4 Sonnet
Anthropic’s efficient AI model balancing speed, cost, and fluency for conversational and creative tasks.
Claude 4 Opus
Anthropic’s most powerful model for deep reasoning, knowledge tasks, and enterprise AI applications.
LLaMA-4
Meta’s next-generation language model with enhanced scalability and strong performance in NLP tasks.
Mistral 7B
A lightweight, high-performance open model optimized for efficiency and fast text generation.
Cohere Command R+
Cohere’s leading reasoning model, fine-tuned for RAG (retrieval-augmented generation) and enterprise use cases.
DeepSeek-R1
A reasoning-focused AI model designed for coding, math, and logic-intensive tasks.
Google Gemini Flash
Google’s lightweight Gemini family model optimized for speed and multimodal generation.
Whisper V3
OpenAI’s high-accuracy speech-to-text model for transcription and voice applications.
Stable Diffusion
A generative model enabling controlled and customizable image creation & editing.
DALL-E 3
OpenAI’s image generation model creating detailed visuals from natural text prompts.
Phi-2
Microsoft’s small, efficient multimodal AI model advancing text and image generation.
FAQs
Generative AI development services
What makes Markovate the right partner for Generative AI development?
We combine deep AI/ML expertise with hands-on product engineering experience. Our team has built Generative AI solutions across industries like healthcare, insurance, and fintech focusing on measurable business impact, scalability, and responsible AI deployment.
Do you build fully custom Generative AI solutions or integrate existing models?
Both. We fine-tune and integrate leading LLMs like GPT, Claude, and Llama for domain-specific needs, or develop fully custom Generative AI systems when proprietary data and control are essential. Our goal is always to align with your infrastructure, security, and performance requirements.
What is your typical engagement process for Generative AI projects?
We start with a discovery and strategy phase to define use cases and success metrics, followed by model design, integration, and validation. You get an initial proof-of-concept in 4–6 weeks, then we scale based on business results and ROI alignment.
How do you ensure data security, compliance, and IP protection?
Every Generative AI project follows strict data governance, encryption, and privacy protocols. We ensure compliance with GDPR, HIPAA, and SOC 2 where required. All models and code built for your project remain your intellectual property.
OUR BLOGS
Point of view
Our thought leadership initiative – an exclusive platform for sharing our insights and technological perspectives.
On-device LLMs: The Disruptive Shift in AI Deployment
Large Language Models (LLMs) have reshaped how we interact with technology, powering everything from smart search to AI writing assistants. But until now, their power has mostly lived in the cloud. That’s starting to change. On-device LLMs are bringing this...
ERP Automation 2.0: How Generative AI Is Reshaping ERP
ERP automation has powered enterprise operations for decades, but they have struggled to keep up with today’s speed, complexity, and scale. Manual data entry, fragmented workflows, and inaccurate forecasts have long held back their full potential. Now, Generative AI...
Diffusion LLMs (dLLMs): Introducing a New Generation of LLMs
Diffusion LLMs: Introduction In a world where we have relied on autoregressive models to drive AI, a new approach is quietly gaining momentum- Diffusion Large Language Models (dLLMs or diffusion LLMs). Unlike the models we are used to, which predict text one word at a...
Quantum Computing Applications: Top Industry Use Cases
Quantum computing is no longer a lab experiment — it's entering real business operations. Industries like finance, healthcare, logistics, and manufacturing are already running pilots and seeing measurable results. The global quantum computing market is expected to...