Services
How We Help You Build AI POC
AI Strategy & Roadmap Planning
We begin by working closely with you to assess technical viability and validate ROI before any heavy build. You’ll receive a clear roadmap plan for your AI PoC journey that aligns with your business goals and minimizes risk
Data Processing & Preparation
Your AI is only as good as its data. We audit your existing infrastructure, then collect, clean, and preprocess the data you need. It makes sure that your models are built on a reliable and scalable foundation
PoC Rapid Prototyping
We take your idea and bring it to life in a working prototype. In rapid sprints, we test integration, performance, and key assumptions. You get an early model that shows what works and where the value lies before full development
AI Model Development
Once the PoC direction is clear, we train and validate AI models based on your use cases. Through rigorous testing and quality assurance, we make sure they perform reliably and meet compliance standards
Integration & Deployment
With your PoC validated and models polished, we integrate the AI solution with your existing systems and deploy in your environment
Use Case
Addressing Key Business Challenges
Find out how our AI solutions address common business pain points
You’re unsure whether an AI concept like document analysis will work with your data
Build a PoC to test model accuracy, resource usage, integration constraints, and viability before fully committing
You lack clarity on which AI features to prioritize first
We help you select, prioritize, and prototype the highest-impact and lowest-risk feature first as MVP
You fear your system, data, or compliance constraints will block AI deployment
In the PoC phase, we run experiments within your constraints to expose issues early, not after full build
You're afraid of long development cycles and going into a black box
To keep you informed and involved, we use transparent, iterative development and frequently demo results
Benefits
Test User Experience in Real Time
See how customers and teams interact with the prototype to refine usability and adoption
Minimize Risk
Early detection of technical flaws, legal concerns, and scalability issues will help you invest only in AI solutions that will yield the best return on investment
Validate Feasibility
Before launching your AI concept on a large scale, make sure it is feasible and fits with your strategic objectives
Data-Driven Decisions
Obtain quantifiable results and transparent success metrics that direct planning, budgeting, and the following stage of development
Scalability and Market Fit
Create an AI system that fits real-world user needs right away and scales seamlessly throughout your company
Industries
Achieve More with Purpose-Built Applications
Advance your business with these applications that deliver precision, personalization, and measurable value at every step.
Chatbots & Virtual Assistants
Recommendation Engine
Predictive Maintenance
Healthcare Diagnostics
Voice & Speech Recognition
Chatbots & Virtual Assistants
Customers can get instant answers without waiting in a queue. A PoC chatbot shows how AI can resolve routine queries and keep your support team focused on what matters most.
- Human-like replies with accurate language understanding
- Continous support on web and mobile
- Quick CRM and ticketing integration
Recommendation Engine
Deliver the right product or content to every user. A PoC recommender proves how AI can boost engagement and sales by learning individual preferences in real time.
- Content-based filtering
- Real-time personalization across channels
- Uplift in conversions and customer loyalty
Predictive Maintenance
A predictive-maintenance PoC analyzes sensor data to warn you before failures occur, so you can plan service only when it’s truly needed
- Real-time anomaly detection on IoT data
- Optimized maintenance schedules
- Actionable alerts sent to existing monitoring dashboards
Healthcare Diagnostics
Help clinicians make fast and data-driven decisions. A diagnostic PoC analyzes scans or patient data to highlight potential issues and suggest next steps.
- Analysis of X-rays, MRIs, or lab results
- Early detection for improved patient outcomes
- Integrates securely with EHR systems
Voice & Speech Recognition
A speech-recognition PoC turns conversations into text and understands commands to create hands-free experiences for users.
- Accurate real-time transcription
- Multi-language support
- Speaker identification and sentiment analysis
Our Process
Fine-tuning LLM Models in 4 Simple Steps
Whether you're enhancing accuracy, aligning tone, or utilizing domain-specific knowledge, the fine-tuning process can be broken down into the following stages
Requirement Analysis
We start by defining the technical requirements and determining the main use cases. This includes understanding data sources, expected model behavior, infrastructure compatibility, and performance benchmarks.
Model Selection & Customization
Based on the analysis, we select the most suitable LLM (GPT, BERT, or other specialized models) and fine-tune it with domain-specific data. Hyperparameter tuning, prompt engineering, and performance optimization are applied to align the model’s output with your use case.
System Integration & Testing
We build APIs and deploy the model within your infrastructure, to ensure smooth integration with existing workflows, databases, and applications. Rigorous testing is conducted to evaluate response accuracy, latency, and system load under different conditions.
Deployment & Maintenance
The model is deployed into a production environment with continuous performance monitoring in place. We implement feedback loops, version control, and regular updates to keep the model accurate, efficient, and aligned with evolving business needs.
Real-World Impact
Intelligence That Delivers Tangible ROI
25%
higher long-term ROI when scaling AI projects that were pre-tested through a PoC.
40%
reduction in project risk through early detection of data, compliance, and scalability issues.
FAQs
Got questions? We’re here with every answer you need!!
Explore these quick answers to help you better understand our solutions and how they work!
The cost of developing an AI PoC varies depending on the complexity of the project, the technology used, and the specific requirements of your business. Generally, the cost can range from a few thousand to tens of thousands of dollars.
You’ve Been Thinking About It for Weeks. Let’s Talk!
Bring your complex ideas, half-scoped plan, or big ambition. We’ll help you sort it out.
Let's Discuss Your Project!
Share the details of your project – like scope or business challenges. Our team will carefully study them and then we'll figure out the next move together.