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LLM Development Services

Turn LLM potential into production-ready solutions built around your data, business processes, and measurable outcomes.

Plan Your LLM Solution

LLM Development Experience That Drives Business Impact

50+
Enterprise Project Delivered
40+
Global Businesses Supported
175+
Engineers & Technology Experts
3+
Years of Engineering Expertise
15+
Industry Transformed

Build Smarter With Our Enterprise LLM Development Expertise

End-to-end LLM development capabilities to turn language models into practical, secure, and production-ready business solutions.

LLM Consulting & Strategy

Assess which opportunities, use cases, and approaches to LLM implementation are best for your business. Strategy includes use-case evaluation, data preparation, architectural design, choice of technology, security considerations, and the path forward from pilot to production.

Custom LLM Development

Develop LLM solutions using your data, specialized terminology, workflow, answer format, and efficiency needs. The right blend of foundation models, open source models, RAG, fine tuning, agents, and other supporting AI components is chosen for each use case.

LLM Fine-Tuning & Customization

Adapt pre-trained models to specialised domains, terminology, workflows, structured outputs, classification, and task-specific requirements. Techniques such as LoRA, QLoRA, and PEFT can provide targeted customisation and balance performance, infrastructure, and cost.

RAG Development

Connect LLMs with enterprise knowledge and appropriate data through RAG. Solutions can involve document handling, embeddings, vector database, semantic search, hybrid search, reranking, context handling, and response grounding.

LLM Application Development

Turn LLM capabilities into applications designed around specific business needs and user workflows. Solutions include enterprise assistants, conversational AI, intelligent search, document intelligence, research applications, and AI-powered business platforms.

AI Agent & Copilot Development

Extend LLM applications with agents and copilots capable of retrieving information, using tools, calling APIs, executing multi-step tasks, and interacting with enterprise systems. Permissions, business rules, and human oversight can be built into agent workflows.

Multimodal LLM Development

Develop AI models that work with all forms of data from text, documents, imagery, audio, etc. The use case applications include document processing, computer vision, voice interfaces, research use cases, and intelligent customer interactions.

LLM Integration & Deployment

Integrate LLM solutions with CRMs, ERPs, databases, APIs, knowledge bases, customer platforms, and any software. This deployment can be done in a public, private or hybrid cloud or even controlled on-premise environment depending on various requirements.

LLM Evaluation & Optimisation

Improve the reliability and performance of production LLM applications through structured evaluation and optimisation. Assessment can cover accuracy, relevance, groundedness, factuality, safety, latency, consistency, task performance, and cost, followed by prompt, retrieval, or model-level improvements.

LLM Security & Governance

Establish security and governance controls across data, applications, users, models, and infrastructure. Measures can include access controls, data protection, prompt-injection protection, AI guardrails, output validation, auditability, monitoring, privacy controls, and governed deployment.

LLMOps & Managed Services

Keep production LLM environments reliable and efficient as models, data, workloads, and business requirements evolve. Ongoing services can cover monitoring, evaluation, model and prompt updates, retrieval optimisation, infrastructure management, cost tracking, troubleshooting, and continuous performance improvement.

Ready to Build an LLM Solution That Delivers?

Turn your LLM opportunities into secure, scalable, production-ready AI solutions tailored to your data, workflows, and business goals.

Build Your LLM Solution

How Can LLMs Transform Your Industry?

Our LLM solutions can be adapted to the requirements, data environments, and workflows of different industries.

BFSI
  • Customer support automation
  • Document analysis
  • Compliance assistance
  • Decision-support solutions
Healthcare & Life Sciences
  • Clinical documentation
  • Knowledge assistants
  • Administrative automation
  • Patient information support
Retail & E-commerce
  • Product discovery
  • Personalised experiences
  • Customer support
  • Marketing content assistance
Manufacturing
  • Technical assistants
  • Knowledge management
  • Operational documentation
  • Process support
Logistics & Supply Chain
  • Document processing
  • Workflow assistance
  • Operational intelligence
  • Supply chain knowledge support
Legal & Professional Services
  • Contract analysis
  • Policy Q&A
  • Enterprise knowledge assistants
  • Legal document assistance
Education
  • Content generation
  • Learning assistants
  • Knowledge platforms
  • Administrative support
Telecom
  • Customer service
  • Knowledge management
  • Network support
  • Technical troubleshooting

Turn Industry Challenges Into LLM-Powered Solutions

Build Your Industry Solution
  • Automate compliance and customer support
  • Streamline administrative workflows
  • Personalize engagement, and experiences
  • Connect knowledge with operations
  • Simplify workflows, and supply intelligence
  • Accelerate service and network support

LLM Solutions Built Around Privacy, Risk & Responsible Use

LLM applications expose prompts, retrieved knowledge, context, tools, and outputs to new forms of misuse and data exposure. Xcelore applies controlled data boundaries, evaluation, response checks, and access practices according to the sensitivity and purpose of the deployment.

Compliance

OWASP Top 10 for LLM Applications

NIST AI RMF

ISO/IEC 42001

ISO/IEC 27001

SOC 2

DPDP Act

CCPA/CPRA

PDPL

GDPR

LLM Solutions We Build for Business Applications

From employee productivity to customer engagement and operational efficiency, LLM solutions can be tailored to the way your organisation works, communicates, and makes decisions.

Enterprise Knowledge Assistants

Give employees a faster way to access and work with organisational knowledge. These solutions can help locate information, answer questions, summarise internal content, and support everyday decision-making across distributed knowledge sources.

AI Chatbots & Virtual Assistants

Create conversational experiences that help customers and employees get answers, complete routine requests, and navigate digital services. Experiences can be designed for websites, applications, portals, and other customer or employee touchpoints.

Intelligent Enterprise Search

Make large volumes of business information easier to discover and use. Natural-language search can help users find relevant insights across internal content without relying on rigid keywords or navigating multiple information repositories.

Document Intelligence

Turn business documents into structured, usable information and insights. Solutions can support document classification, information extraction, comparison, summarisation, and analysis across contracts, invoices, reports, forms, policies, and research material.

Content Intelligence

Accelerate content-heavy workflows with AI-assisted creation and transformation. Applications can support summarisation, translation, personalisation, classification, rewriting, and content adaptation while following defined organisational standards.

Customer Service Automation

Improve service operations by assisting teams with routine customer interactions and support activities. Capabilities can include response assistance, request categorisation, conversation summaries, knowledge support, and intelligent handoffs for cases requiring human attention.

Developer & Engineering Assistants

Help engineering teams work more efficiently across the software development lifecycle. AI assistants can support coding tasks, technical documentation, test creation, code understanding, debugging, and access to development knowledge.

LLM-Powered Workflow Automation

Reduce manual effort across information-intensive business processes. LLM-powered workflows can support activities such as request handling, document processing, classification, summarisation, approvals, and operational task coordination.

Domain-Specific LLM Applications

Apply language intelligence to specialised business environments where generic solutions may not provide the required relevance or control. Applications can be tailored to industry-specific terminology, processes, regulatory contexts, and organisational requirements.

Turn Language Intelligence Into Business Impact

Move beyond LLM experimentation with enterprise-ready LLM development built for accuracy, security, scalability, and real-world performance. Xcelore helps you build intelligent LLM applications aligned with your business goals, data, workflows, and technology environment.

Technologies Behind Our LLM Services

OpenAI

Anthropic Claude

Google Gemini

Llama

Mistral

Hugging Face

LangChain

LangGraph

LlamaIndex

Semantic Kernel

CrewAI

Pinecone

Weaviate

Milvus

pgvector

Redis

Elasticsearch

Qdrant

vLLM

NVIDIA Triton

MLflow

LangSmith

OpenTelemetry

OpenAI

Anthropic Claude

Google Gemini

Llama

Mistral

Hugging Face

LangChain

LangGraph

LlamaIndex

Semantic Kernel

CrewAI

Pinecone

Weaviate

Milvus

pgvector

Redis

Elasticsearch

Qdrant

vLLM

NVIDIA Triton

MLflow

LangSmith

OpenTelemetry

Our Proven Approach to Building Production-Ready LLMs

A structured engineering process keeps business objectives, technical decisions, and production requirements aligned throughout development.

Discover

Define the business problem, users, workflows, data sources, success criteria, and technical constraints.

Design

Create the application and data architecture, determine the model strategy, and define retrieval, integration, security, and deployment requirements.

Engineer

Build the application, connect enterprise data and systems, implement required AI capabilities, and establish the supporting infrastructure.

Validate

Test the solution against business scenarios and technical benchmarks covering quality, security, reliability, latency, and cost.

Deploy & Improve

Move the validated solution into production with monitoring and operational controls, then continuously improve it using real-world performance data.

Why Leading Organisations Choose Xcelore for LLM Engineering

Business-Outcome Focus

Start with the business problem and expected outcome rather than selecting a model first.

Full-Stack Engineering

Combine LLM engineering with application development, data engineering, cloud, DevOps, APIs, and enterprise integration.

Model Flexibility

Work across proprietary and open-source models so the architecture can evolve as models, costs, and requirements change.

Production Engineering

Design beyond the proof of concept with evaluation, observability, security, integration, and operational readiness considered from the start.

End-to-End Delivery

Support the journey from initial LLM strategy through development, deployment, optimisation, and ongoing operations.

Let’s talk

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Frequently Asked Questions

How does a custom LLM solution differ from an off-the-shelf AI tool?

An off-the-shelf tool is built for general use and shared across many customers with limited configurability. A custom LLM solution is grounded, fine-tuned, or retrieval-augmented on your proprietary data, rules, and terminology, which produces higher accuracy, more control, and outputs aligned with how your business actually operates.

We don't have in-house AI expertise, can you still help us scope the right approach?

Yes. Engagements typically begin with a discovery and consulting phase that assesses your goals, data, and risk profile, and results in a model and architecture recommendation with a phased roadmap, no prior AI expertise required on your side.

Can an LLM solution integrate with our existing CRM, ERP, or internal tools?

Yes. Integration and deployment work covers connecting the LLM application to systems such as CRMs, ERPs, internal APIs, and existing knowledge repositories, so the solution fits into how your teams already work rather than requiring a workflow change.

What do you do to reduce hallucinations and unreliable outputs?

We reduce hallucination risk through data grounding, retrieval-augmented generation, task-specific fine-tuning where warranted, output validation layers, and evaluation pipelines that measure factuality and groundedness against a defined test set — rather than relying on prompting alone.

How long does an initial engagement typically take?

Timelines vary by scope. A focused proof of concept can typically be validated in a matter of weeks; a production-ready application depends on integration complexity, data readiness, and evaluation requirements and is scoped during discovery.

Ready to Put LLMs to Work?

Turn Language Intelligence Into Business Impact.

Build secure, scalable LLM solutions that transform enterprise data, automate complex workflows, enhance customer experiences, and deliver measurable business value across your organization.