Generative AI development services
Leverage smart Generative AI solutions for effortless problem-solving.
Innovative solutions, swift outcomes
Harness the power of algorithms and machine learning with our Generative AI solutions to boost efficiency and creativity. Enhance your digital presence, improve customer experience (CX), and automate complex tasks. Here’s how we can help:
Predictive Analytics.
Utilize GenAI for data-driven foresight and strategic planning.
Natural Language Processing.
Overcome communication challenges and simplify tasks with conversational interfaces.
Image & Video Analysis.
Harness visual data to unlock transformative insights and enhance efficiency.
Personalized Recommendation Systems.
Wow your customers with personalized experiences and strategic content solutions.
Why seek support with Generative
AI Development?
Our partners have experienced faster decision-making, enhanced customer experiences, streamlined operations, and reduced costs through the power of Generative AI. Here are some of the businesses we’ve serviced:
In our clients' words
We reached out to Xeltec in March 2019 and asked them to provide us with a proof of concept for a new subsystem that we were building. They rose to the challenge and delivered a great POC in the four-week timeframe. Since, that time Xeltec has been a great partner for us. They are an integral part of both our architecture and development teams. We will continue to expand our Xeltec team in 2020 and we look forward to growing with them.
David Gay /
Head of Engineering
Working with Xeltec has been a great collaboration is more than an understatement. They are
engaging, interactive and futuristic. They are always a step ahead of the game. The inhouse
support is always there around the clock to keep us updated about the process.
Sam Kahanov / Head of Product Management
An autonomous document management system empowering businesses to reclaim valuable time and resources
Upmonth is a cutting-edge autonomous system streamlining document organization for investors and investment companies. It centralizes documents, applies tags, and enables instant retrieval using machine learning.
Primary challenges we overcome
Simplifying complex system architecture.
Pavemint faced intricate architecture issues; we streamlined functionality with scalable tools, a repository, and GraphQL APIs.
Strengthening system documentation.
Insufficient documentation hindered operations; we delivered self-documenting APIs and streamlined processes for seamless maintenance.
Improving system reliability.
Frequent disruptions plagued users; we implemented centralized tools and SSO for smooth operations and enhanced user experience.
Modernizing legacy systems.
Outdated WPF/WCF systems limited scalability; we created mobile-friendly solutions to ensure compatibility with modern technologies.
Tackling integration and scalability issues.
Lack of hardware and third-party integration caused inefficiencies; we ensured compatibility, scalability, and seamless communication.
Enhancing patient care with technology.
Heartbeat Health needed efficient cardiovascular care tools; we delivered secure communication, vitals tracking, and smart device integration.
Why Xeltec?
0
+
Years in the market
0
+
People on board
0
+
Projects delivered
0
NPS score
Gain insights for quick advancement
Imagine, Innovate, Automate – With GenAI
Curious about the impact of GenAI on your business? Here are some top questions our clients explore when assessing its potential.
What is Generative AI?
Generative AI is an innovative branch of artificial intelligence that focuses on producing new and unique content or data. Unlike traditional AI that primarily analyzes existing information, Generative AI uses advanced algorithms to create outputs such as text, images, audio, video, and even complex structures like molecules. By identifying patterns in training data, it generates original outputs that are inspired by but not duplicates of the source material.
What are real-world applications of Generative AI across industries?
Generative AI is driving change across industries with its multifaceted applications:
- Marketing and Content Creation: Producing creative marketing materials, personalized advertisements, scripts, poetry, or even composing music.
- Image and Video Production: Crafting realistic stock images, producing product variations, developing lifelike game textures, or improving visual quality.
- Healthcare: Discovering drug candidates, creating synthetic medical images for training, and tailoring treatment plans.
- Finance: Predicting markets, managing risks, detecting fraud through anomaly detection, and generating synthetic datasets for privacy-safe training.
- Software Development: Automating code generation, translating programming languages, and creating software documentation.
What are the key steps to developing a Generative AI solution?
Creating a robust Generative AI solution involves the following stages:
- 1. Identify Business Objectives: Define goals, audience, desired outcomes, and performance metrics.
- 2. Data Preparation: Gather, clean, and process data; use data augmentation if required.
- 3. Model Selection: Choose the appropriate model based on data type and goals.
- 4. Development and Training: Design the architecture, select algorithms, and train the model iteratively while fine-tuning.
- 5. Evaluation and Refinement: Measure performance against metrics, refine as needed.
- 6. Deployment and Integration: Implement the model in infrastructure, ensure scalability, and address security concerns.
- 7. Monitoring and Maintenance: Track performance, update with new data, and retrain for relevance.
What are the key technologies and tools for Generative AI Development?
Generative AI relies on a range of tools and technologies:
- Programming Languages: Python and R for their robust libraries.
- Deep Learning Frameworks: TensorFlow, PyTorch, and Keras for building and training networks.
- Generative AI Tools: StyleGAN2, Stable Diffusion, Disco Diffusion for specialized generative tasks.
- Large Language Models: GPT-4, PaLM, and Jurassic-1 Jumbo for language-based applications.
- Cloud Services: Platforms like GCP, Azure, and AWS for scalable AI model training and deployment.
What should be considered when deploying and maintaining a Generative AI model?
- 1. Scalability: Ensure systems handle growth in traffic and data.
- 2. Security and Privacy: Protect sensitive data and comply with regulations like GDPR or HIPAA.
- 3. Explainability: Use explainable AI (XAI) techniques for transparency and trust.
- 4. Continuous Learning: Monitor performance, incorporate new data, and retrain as needed.
What are the benefits for businesses working with a Generative AI Development company?
- Expertise: Access to professionals skilled in Generative AI models and strategies.
- Customized Solutions: Tailored applications that fit unique business needs.
- Speed to Market: Pre-built frameworks accelerate development and deployment.
- Cost Efficiency: Optimized resource use and avoidance of common pitfalls.
- Ongoing Support: Post-launch assistance ensures accuracy, relevance, and security.
Contact our expert
Partnering with Xeltec means laying the groundwork for products that thrive in today’s market while being prepared for future opportunities.