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
No. 70% of Ubikon AI projects use pre-trained LLMs (GPT-4, Claude, Gemini) with RAG over your existing documents, databases, or knowledge bases. No training data needed. Custom model fine-tuning requires 1,000 to 10,000 labeled examples and adds 2 to 4 weeks to the timeline.
AI development at Ubikon costs: Starter AI feature or chatbot from ₹3L (6 to 8 weeks), full AI System from ₹7L (8 to 12 weeks), Enterprise AI with custom training from ₹22L (12 to 24 weeks). Ongoing inference costs: typically ₹5,000 to ₹50,000/month depending on query volume.
Ubikon works with OpenAI (GPT-4o, GPT-4, o1), Anthropic (Claude 3.5 Sonnet, Opus), Google (Gemini 1.5 Pro), and open-source (Llama 3, Mistral, Phi-3). Model selection is based on 3 factors: accuracy on your use case, per-token cost, and data privacy requirements.
Ubikon uses 5 guardrails to prevent hallucinations: (1) RAG grounding in verified sources, (2) output schema validation with Zod/Pydantic, (3) confidence scoring with abstention below 0.7, (4) human-in-the-loop for high-stakes decisions, and (5) weekly red-team testing during development.
Yes. For healthcare, finance, legal, and defense clients, Ubikon deploys open-source models (Llama 3 70B, Mistral Large) on your own AWS/Azure/on-prem infrastructure. Zero data leaves your environment, zero third-party API calls. HIPAA/SOC 2/GDPR compliant out of the box.
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.
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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.