Custom AI Systems
That Actually Work
We build battle-tested AI systems: LLM integrations, intelligent chatbots, automation pipelines, and computer vision, using GPT-4, Claude, Gemini, and Llama 3.
40+
AI Systems Built
99.2%
Avg Accuracy
10x
Avg Productivity Gain
₹3L+
Starting From
What We Deliver
Every engagement includes these core deliverables.
LLM Integration
Custom GPT-4, Claude, Llama, and Mistral integrations with fine-tuning, RAG pipelines, and prompt engineering.
AI Chatbots & Assistants
Intelligent conversational AI with context memory, tool use, and multi-step reasoning for customer service and internal tools.
Process Automation
End-to-end automation of document processing, data extraction, classification, and workflow orchestration.
Computer Vision
Image/video analysis, OCR, object detection, and visual inspection systems built with PyTorch and TensorFlow.
Predictive Analytics
ML models for forecasting, churn prediction, recommendation engines, and anomaly detection.
AI Safety & Moderation
Content moderation, output validation, hallucination detection, and responsible AI guardrails.
Our Tech Stack
We use battle-tested technologies chosen for performance, scalability, and speed.
LLM Providers
ML Frameworks
Vector Databases
Backend
Infrastructure
Data
Our Process
A proven 6-step process refined over 300+ projects. Clear milestones, no surprises.
Week 1
AI Strategy & Data Audit
Understand your use case, evaluate data quality, select the right models, and define success metrics.
Week 2
Proof of Concept
Build a working prototype to validate the approach before full development begins.
Week 3 to 6
Model Development
Fine-tuning, RAG pipeline setup, integration development, and iterative testing with real data.
Week 7
Evaluation & Red-teaming
Accuracy benchmarking, hallucination testing, edge case handling, and safety evaluation.
Week 8
Production Deployment
API deployment, monitoring setup, rate limiting, cost optimization, and failover handling.
Ongoing
Monitoring & Improvement
Model performance tracking, feedback loops, retraining pipelines, and cost optimization.
Transparent Pricing
No hidden costs. Fixed-price or milestone-based. You choose.
Starter AI
From ₹3L
6 to 8 weeks
Single AI feature or chatbot integration for your existing product.
- LLM API integration
- Custom prompt engineering
- Basic RAG pipeline
- REST API endpoint
- Monitoring dashboard
- 30-day support
AI System
From ₹7L
8 to 12 weeks
Full AI product or automation system with multiple capabilities.
- Everything in Starter
- Multi-model pipeline
- Vector database
- Fine-tuning
- Custom UI/dashboard
- Training data pipeline
- 90-day support
Enterprise AI
Custom
12 to 24 weeks
Large-scale AI transformation with custom models and deep integrations.
- Everything in AI System
- Custom model training
- On-premise deployment
- Enterprise security
- Dedicated ML engineer
- 12-month support
LogiFlow: AI Document Processing
50,000 Documents Processed Daily at 99.2% Accuracy
"Ubikon built an AI pipeline that processes 50,000 documents daily with 99.2% accuracy. Our team productivity increased 10x."
Marcus Thompson
CTO, LogiFlow (UK)
Related Case Studies
See how we delivered results for clients with similar needs.
Frequently Asked Questions
Helpful Resources
Tools, comparisons, and guides to help you plan your build.
Pricing & Packages
Fixed-price tiers from ₹2.5L MVP to ₹40L enterprise.
Cost Calculator
Instant estimate based on features and complexity.
Case Studies
Real projects with measurable outcomes.
Compare Hiring Models
Freelancer vs agency vs Ubikon — cost, quality, risk.
Why Ubikon
Fixed pricing, 48-hour proposals, 300+ projects.
Engineering Blog
Technical guides on AI, mobile, SaaS, and startups.
Start Your Project Today
Get a free AI-powered proposal in 24 hours. No commitments, no hidden costs.
🕐 Response within 2 hours · 💼 NDA available · 🌍 All time zones
AI development company in India
Ubikon Technologies is an Indore, India–based AI development company (founded 2016) that builds custom AI systems: LLM (large language model) integrations, intelligent chatbots and assistants, process automation pipelines, computer vision, and predictive analytics. We work across GPT-4, Anthropic Claude, Google Gemini, and open-source Llama 3 and Mistral, selecting the model based on accuracy, per-token cost, and data-privacy requirements. Around 70% of our AI projects use pre-trained LLMs with RAG (retrieval-augmented generation) over your existing documents and databases, so no training data is required.
A single AI feature or chatbot starts from ₹3L and ships in 6–8 weeks; a full multi-capability AI system starts from ₹7L (8–12 weeks); and enterprise AI with custom model training is delivered in 12–24 weeks. Every engagement is a fixed-price contract, and you own 100% of the source code and IP with an IP-assignment agreement signed before day one and an NDA on request. We ship with real guardrails — RAG grounding, output schema validation, confidence scoring, and red-team testing — and can deploy open-source models on-premise for healthcare, finance, and legal clients. We return a free proposal within 24–48 hours.
- LLM integration with GPT-4, Claude, Gemini, Llama 3 & Mistral
- RAG pipelines & fine-tuning over your own data — no training set needed
- AI chatbots, process automation, computer vision & predictive analytics
- 5 hallucination guardrails incl. RAG grounding + red-team testing
- On-premise open-source deployment for HIPAA/SOC 2/GDPR needs
- 100% source code + IP ownership, fixed-price, NDA on request
Frequently asked questions
- How much does AI development cost in India?
- A single AI feature or chatbot (Starter AI) starts from ₹3L in 6–8 weeks, a full AI System from ₹7L in 8–12 weeks, and Enterprise AI with custom training runs 12–24 weeks at custom pricing. Ongoing inference typically costs ₹5,000–₹50,000/month depending on query volume. Ubikon quotes a fixed price upfront.
- Do I need my own data to build an AI system?
- No. Around 70% of Ubikon AI projects use pre-trained LLMs (GPT-4, Claude, Gemini) with RAG (retrieval-augmented generation) over your existing documents, databases, or knowledge bases — no training data required. Custom model fine-tuning needs 1,000–10,000 labeled examples and adds 2–4 weeks.
- How do you prevent AI hallucinations?
- Ubikon uses five guardrails: RAG grounding in verified sources, output schema validation with Zod/Pydantic, confidence scoring with abstention below 0.7, human-in-the-loop for high-stakes decisions, and weekly red-team testing during development.
- Can AI be deployed on-premise for data privacy?
- Yes. For healthcare, finance, legal, and defense clients, Ubikon deploys open-source models such as Llama 3 70B and Mistral Large on your own AWS, Azure, or on-prem infrastructure — no data leaves your environment and no third-party API calls are made. It is HIPAA, SOC 2, and GDPR compliant.