Generative AI Development Services

Custom generative AI solutions including LLM fine-tuning, RAG architectures, AI agents, and enterprise ChatGPT-like applications built for production.

50+
AI Solutions Deployed
95%
Response Accuracy
60%
Avg Cost Reduction
48hrs
Proof of Concept Start

Why Choose Cozcore for Generative AI Development

Cozcore builds production-grade generative AI solutions that go far beyond simple API wrappers. Our team designs and implements custom LLM-powered applications, RAG architectures, and AI agent systems that deliver measurable business value while meeting enterprise requirements for security, reliability, and governance.

Our approach starts with a deep understanding of your data and workflows. We architect Retrieval-Augmented Generation (RAG) pipelines that ground LLM responses in your proprietary knowledge, fine-tune open-source and commercial models on your domain-specific data, and build multi-step AI agents that autonomously execute complex tasks. Every solution is engineered for production with proper guardrails, evaluation frameworks, and monitoring.

With experience deploying generative AI across healthcare, finance, legal, and e-commerce, we understand the unique challenges of each industry. Our solutions include robust data privacy controls, content filtering, hallucination detection, and audit trails that satisfy compliance requirements. Whether you need an enterprise knowledge assistant, an AI-powered customer support system, or a document processing pipeline, we deliver generative AI that is accurate, safe, and scalable.

Our Generative AI Development Services

Comprehensive solutions tailored to your business needs

🧬

LLM Fine-Tuning & Training

Domain-specific fine-tuning of open-source and commercial LLMs using your proprietary data, with evaluation benchmarks and continuous improvement pipelines.

🔍

RAG Architecture Design

Production-grade Retrieval-Augmented Generation systems with advanced chunking strategies, hybrid search, re-ranking, and citation tracking for accurate, grounded responses.

🤖

AI Agents & Copilots

Autonomous AI agents and domain-specific copilots that execute multi-step workflows, integrate with external tools, and make decisions within defined guardrails.

💬

Prompt Engineering & Optimization

Systematic prompt design, testing, and versioning frameworks that maximize model performance, reduce token costs, and ensure consistent output quality.

🖼️

Multi-Modal AI Solutions

Applications combining text, image, audio, and video understanding for document analysis, visual search, content generation, and multimodal knowledge extraction.

🛡️

AI Governance & Safety

Enterprise-grade guardrails including content filtering, hallucination detection, PII redaction, bias monitoring, and comprehensive audit trails for responsible AI deployment.

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Industry Applications

We deliver generative ai development solutions across diverse industry verticals

Healthcare & Life Sciences

Clinical documentation assistants, medical literature analysis, patient communication automation, and drug interaction knowledge bases with HIPAA-compliant architectures.

Financial Services

Regulatory document analysis, financial report generation, risk assessment copilots, and compliance monitoring powered by domain-specific LLMs.

Legal & Compliance

Contract review and analysis, legal research assistants, regulatory change detection, and automated document drafting with citation verification.

E-Commerce & Retail

AI-powered product descriptions, personalized shopping assistants, customer support automation, and intelligent product recommendation through conversational interfaces.

Education & Training

Adaptive learning tutors, automated content generation, student assessment analysis, and intelligent course recommendation systems.

Manufacturing & Industrial

Technical documentation assistants, maintenance knowledge bases, quality control report generation, and supply chain intelligence systems.

Technology Stack

Enterprise-grade technologies powering our generative ai development solutions

OpenAI Claude LangChain LlamaIndex Hugging Face FastAPI Pinecone ChromaDB

Our Development Process

A battle-tested methodology refined over 200+ successful projects

1

AI Strategy & Assessment

Evaluate your data assets, identify high-impact use cases, assess feasibility, and create a prioritized roadmap for generative AI implementation.

JupyterMiroLangSmithConfluence
2

Data Preparation & Curation

Clean, structure, and curate your knowledge base for optimal retrieval. Design chunking strategies, metadata schemas, and embedding pipelines.

LlamaIndexUnstructuredLabel StudioApache Airflow
3

Model Selection & Architecture

Evaluate and benchmark candidate models against your requirements. Design the end-to-end architecture including retrieval, generation, and orchestration layers.

OpenAIClaudeHugging FaceLangChain
4

Development & Fine-Tuning

Build the application, fine-tune models on your domain data, implement guardrails, and integrate with existing systems and workflows.

PythonFastAPIPineconeChromaDB
5

Testing & Evaluation

Rigorous evaluation using automated benchmarks, human evaluation, adversarial testing, and domain-expert review to ensure accuracy and safety.

RAGASLangSmithPromptfoopytest
6

Deployment & Monitoring

Production deployment with real-time monitoring of response quality, latency, costs, and user feedback loops for continuous improvement.

AWS BedrockDockerGrafanaLangFuse

Engagement Models

Flexible partnerships designed around your project requirements

AI Proof of Concept

Validate your generative AI use case in 3-5 weeks with a working prototype, evaluation metrics, and a clear roadmap to production.

Ideal for:

Testing AI feasibility, demonstrating value to stakeholders, defining scope

Full AI Product Development

End-to-end development from data preparation through production deployment, including fine-tuning, RAG pipelines, guardrails, and monitoring.

Ideal for:

Enterprise AI products, customer-facing AI features, knowledge management systems

AI Integration Retainer

Ongoing partnership for continuous improvement, model updates, new feature development, and performance optimization of your AI systems.

Ideal for:

Launched AI products needing iteration, expanding AI capabilities, model retraining

Benefits of Our Generative AI Development Services

Automate knowledge-intensive workflows

Reduce operational costs by 30-60%

Improve customer experience with AI-powered interactions

Extract insights from unstructured data at scale

Accelerate content creation and documentation

Why Cozcore

Production-Grade AI

We build AI systems that work reliably at scale, not just impressive demos. Every solution includes guardrails, monitoring, and evaluation frameworks for enterprise deployment.

Security & Privacy First

Enterprise-grade data protection with PII redaction, private deployments, encryption, and audit trails that satisfy healthcare, finance, and legal compliance requirements.

Deep Customization

We fine-tune models on your domain data and build RAG pipelines tailored to your knowledge base, delivering far superior accuracy compared to generic AI solutions.

Full-Stack AI Expertise

From data engineering and model training to frontend integration and DevOps, our team covers the entire AI stack so you get a complete solution from one partner.

Common Use Cases

Solutions we've delivered for businesses like yours

Enterprise Knowledge Bases
AI-Powered Customer Support
Document Processing & Analysis
Code Generation Assistants
Content Creation Platforms

Hire Expert Developers

Scale your team with pre-vetted generative ai development specialists

Get a Detailed Project Estimate

We sign NDA before every engagement. You own 100% of the code.

Related Services

From Our Engineering Blog

Deep-dive technical insights related to generative ai development

Generative AI Development - Frequently Asked Questions

How much does a generative AI project typically cost?
A proof of concept starts at $15,000-$30,000. Production RAG applications range from $40,000-$120,000. Enterprise-scale AI platforms with fine-tuned models and multiple integrations can exceed $200,000. We provide detailed estimates after assessing your data and requirements.
How long does it take to build a production generative AI application?
A proof of concept takes 3-5 weeks. Production RAG applications typically take 8-14 weeks. Complex multi-agent systems with fine-tuned models range from 4-6 months. Timeline depends heavily on data readiness and integration complexity.
How do you handle data privacy and security with LLMs?
We implement multiple layers of protection: PII detection and redaction before data enters the pipeline, private model deployments that keep data within your infrastructure, encryption at rest and in transit, role-based access controls, and comprehensive audit logging. We can deploy entirely on-premise or in your private cloud.
Should we use OpenAI, Claude, or open-source models?
It depends on your requirements. Commercial APIs like OpenAI and Claude offer strong performance with minimal infrastructure. Open-source models like Llama and Mistral provide full data control and lower long-term costs. We often recommend a hybrid approach and help you evaluate based on accuracy, cost, latency, and data privacy needs.
How do you prevent AI hallucinations in production?
We use a multi-layered approach: RAG architectures that ground responses in verified source data, citation tracking so every claim is traceable, confidence scoring to flag uncertain outputs, automated fact-checking against your knowledge base, and human-in-the-loop workflows for high-stakes decisions.
Can you integrate generative AI with our existing systems?
Yes. We build AI solutions that integrate with your existing tech stack through APIs, webhooks, and native connectors. Common integrations include Slack, Teams, Salesforce, Jira, Confluence, SharePoint, custom databases, and internal tools. We ensure the AI fits naturally into existing workflows.

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