AI, LLM & Machine Learning Solutions for Modern Businesses

From LLM-powered applications and RAG pipelines to predictive analytics and computer vision — we build production-ready AI systems that solve real business problems. Serving clients across the USA, UK, Canada, and Australia.

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From LLMs to Legacy ML — We Build It All

The AI landscape has changed dramatically with large language models. Businesses now have access to powerful capabilities — from intelligent chatbots and document understanding to autonomous agents and code generation — that were impossible just a few years ago.

Our AI practice spans the full spectrum: we integrate LLMs like GPT, Claude, and Gemini into your applications, build RAG pipelines over your private data, develop autonomous AI agents, and continue to deliver proven ML solutions like predictive analytics and computer vision.

Whether you need a customer support AI that actually knows your product, a document processing pipeline that reads contracts, or a recommendation engine that drives revenue — we deliver solutions that create measurable business impact.

50+

AI Projects Delivered

95%

Model Accuracy

Efficiency Gains

12+

Industries Served

LLM & Generative AI

Large Language Model Solutions

We help businesses leverage the latest in generative AI — from simple API integrations to complex multi-agent systems.

LLM Integration

Integrate GPT, Claude, Gemini, or open-source LLMs (LLaMA, Mistral) into your existing applications for intelligent search, content generation, summarisation, and more.

RAG Pipelines

Build retrieval-augmented generation systems that ground LLM responses in your private data — documents, databases, wikis, and knowledge bases — for accurate, hallucination-free answers.

AI Agents

Develop autonomous AI agents that can reason, plan, use tools, browse the web, query databases, and execute multi-step workflows with minimal human intervention.

Fine-Tuning & Training

Fine-tune LLMs on your domain-specific data for specialised tasks — legal analysis, medical coding, brand voice, technical documentation, and industry-specific terminology.

Prompt Engineering

Design and optimise prompt templates, chain-of-thought workflows, and system instructions to get the best output quality, consistency, and cost efficiency from any LLM.

AI Chatbots & Assistants

Build intelligent conversational AI that understands context, accesses your knowledge base, handles complex queries, and escalates to humans when needed.

Machine Learning

Traditional AI & ML Services

Proven machine learning solutions for analytics, vision, automation, and data-driven decision making.

Predictive Analytics

Forecast demand, churn, revenue, and market trends with custom ML models trained on your historical data.

Computer Vision

Image recognition, object detection, visual inspection, and video analytics for manufacturing, retail, and security.

Intelligent Automation

AI-powered workflow automation that handles repetitive tasks, document processing, and decision support systems.

Recommendation Engines

Personalised product, content, and service recommendations that increase engagement, upsell, and customer satisfaction.

Natural Language Processing

Sentiment analysis, document classification, text extraction, entity recognition, and language understanding for structured and unstructured data.

Data Engineering & MLOps

End-to-end data pipelines, feature stores, model versioning, automated retraining, and monitoring for production ML systems.

Why GoPanear for AI & LLM Development

We focus on delivering AI solutions that create measurable business impact, not science experiments.

Business-First Approach

We start with your business problem and work backward to the right AI solution, not the other way around.

LLM-Native Engineering

Our team works daily with GPT, Claude, and open-source models. We know prompt patterns, token costs, and failure modes inside out.

Data Privacy & Security

Self-hosted LLM options, data anonymisation, and enterprise-grade security for sensitive industries and regulated data.

Production-Ready Systems

We build for production, not just demos. Every solution includes deployment, monitoring, cost tracking, and fallback handling.

Model-Agnostic

We are not locked to any single provider. We pick the right model for your use case — GPT, Claude, Gemini, LLaMA, Mistral, or custom-trained.

Knowledge Transfer

We train your internal teams to maintain and evolve AI systems, reducing long-term dependency on external vendors.

Frequently Asked Questions

Common questions about our AI, LLM, and machine learning development services.

What types of AI and LLM solutions do you build?

We build a wide range of AI solutions including LLM-powered applications (GPT, Claude, Gemini integrations), RAG pipelines for domain-specific knowledge retrieval, autonomous AI agents, custom chatbots, predictive analytics models, NLP systems, computer vision applications, recommendation engines, and intelligent automation workflows. We also offer LLM fine-tuning and prompt engineering services.

What is RAG and how can it help my business?

RAG (Retrieval-Augmented Generation) combines LLMs with your private data sources — documents, databases, knowledge bases — so the AI generates accurate, context-aware answers grounded in your actual business data. This eliminates hallucinations and makes LLMs useful for enterprise applications like internal knowledge assistants, customer support bots, and document Q&A systems.

Can you integrate LLMs like GPT or Claude into our existing software?

Yes. We integrate LLM APIs (OpenAI, Anthropic Claude, Google Gemini, open-source models) into existing web applications, mobile apps, CRMs, helpdesks, and internal tools. Common integrations include AI-powered search, automated content generation, document summarisation, email drafting, code review assistants, and intelligent form processing.

What is the difference between using an LLM API and fine-tuning?

Using an LLM API with prompt engineering is faster and cheaper — ideal for most use cases. Fine-tuning trains the model on your specific data to improve accuracy for specialised tasks like legal document analysis, medical terminology, or brand-specific tone. We typically recommend starting with prompt engineering and RAG, and only fine-tuning when those approaches hit accuracy limits.

How much does AI or LLM development cost?

A chatbot or LLM integration project typically ranges from $5,000 to $25,000. RAG pipeline development ranges from $15,000 to $50,000. Full-scale AI solutions with custom models, data engineering, and deployment range from $50,000 to $200,000. We recommend starting with a scoped proof of concept to validate the approach before scaling.

How do you handle data privacy and security with AI?

We take data privacy seriously. For sensitive data, we can deploy open-source LLMs on your own infrastructure so data never leaves your environment. For cloud-based solutions, we use enterprise API tiers with data processing agreements, implement data anonymisation, and follow SOC 2 and GDPR compliance practices. All solutions include access controls and audit logging.

Industries we serve

Deep expertise across sectors

Healthcare FinTech Retail & E-commerce Media & Entertainment

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Whether you need a simple LLM integration or a complex AI agent system, let's discuss how AI can transform your business.

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