Reimagine Legal Support Driven by in-Depth Legal Research
- Legal Chatbot Assistant
- Improved Communication Efficiency
- Research Time Reduction by 64%
Reduced Inspection Times for Property Inspectors
- 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
Helped Trapeze Group, Revolutionize Mobility with a Paratransit Solution
- Real-time vehicle tracking
- Advanced algorithms for efficient route planning
- In-app communication interfaces
- Strict adherence to accessibility and privacy laws
Redefining Restaurant Ordering with a Voice Ordering Solution
- State-of-the-art voice recognition
- Provides natural dialogues and verbal responses
- Multi language support for diverse customers
- Dynamic interaction for enhanced engagement
Our enterprise Generative AI development services
Rich expertise across diverse AI models
GPT-5
Claude 4 Sonnet
Claude 4 Opus
LLaMA-4
Mistral 7B
Cohere Command R+
DeepSeek-R1
Google Gemini Flash
Whisper V3
Stable Diffusion
DALL-E 3
Phi-2
Our Generative AI development process for enterprises
Define the problem
Gather Data
Design the model
Train & Evaluate the model
Deploy the model
Monitor and optimize
Define the problem
Gather Data
Design the model
Train & Evaluate the model
Deploy the model
Monitor and optimize
Leading brands we’ve worked with
Our expertise in enterprise Generative AI development
Machine Learning
Our developers possess extensive knowledge and experience in various AI development services. They can proficiently implement machine learning concepts such as predictive modeling, NLP, and deep learning to create robust diffusion model-driven solutions that transform textual data into visual data.
Fine Tuning
Fine-tuning Stable Diffusion models on a smaller dataset can tailor them to a specific task, which is commonly referred to as transfer learning. By doing so, computation and data requirements for training a top-notch model for a particular use case can be reduced.
Deep Learning
Our comprehensive knowledge of deep learning models enables us to leverage multi-layered artificial neural networks to model intricate patterns in data. Moreover, we adeptly utilize the Stable Diffusion deep learning architecture specifically designed for NLP tasks to engineer high-performing solutions.
Transfer Learning
Our area of expertise lies in transfer learning, an AI technology that enables the utilization of pre-trained models on comparable tasks, which enhances performance and reduces training time. We possess a profound understanding of how to leverage pre-trained models to address specific issues, resulting in efficient and effective solutions.
Technology stack we use to build Generative AI enterprise solutions
What our clients say:
About enterprise Generative AI development
How will Generative AI integrate with our existing Enterprise systems and workflows?
What approach do you use for model validation, testing, and performance evaluation?
What regulatory and compliance considerations do you address for Enterprise Generative AI projects?
Can you provide an estimate of the total costs involved in implementing and maintaining the Enterprise Generative AI solution?
What is the expected Return on Investment (ROI) of implementing AI in Enterpise systems?
What is the expected timeline for Enterprise Generative AI development and deployment?
Are there scalability options to accommodate future business growth or changing requirements?
Point of view
AI in Commercial Real Estate: 10 Applications Turning Data Into Growth
Commercial real estate runs on data, from leases and rent rolls to investor reports and market forecasts. Yet for many businesses, this data is scattered across systems and formats, making it difficult to act quickly or confidently. According to Morgan Stanley, AI and...
RFQ Automation in Manufacturing: Powering Smarter, Faster Procurement with AI
Procurement leaders today face a constant squeeze - rising material costs, volatile supply chains, and the pressure to move faster without sacrificing accuracy. Yet for many manufacturers, the RFQ (Request for Quotation) process remains a major bottleneck in...
AI for Manufacturing Quotations: Streamline Quoting, Secure Margins
Traditional quoting processes rely on manually analyzing CAD drawings, extracting material and operation details, and estimating costs and lead times. For complex products, this process can take hours or even days, slowing operations and increasing the risk of errors....
How AI Blueprint Interpretation is Changing Quotation Workflows?
Over the past year, 95% of manufacturers have invested in, or plan to invest in, AI technologies, marking a decisive shift in how design, production, and supply chain workflows are evolving. Meanwhile, traditional automation - macros, scripts, and rule-based processes...
