Generative AI Development Company
Generative AI
Services
for
the Enterprise.
From LLM development and RAG architecture to enterprise AI copilots and intelligent document processing – XFactr.ai builds Generative AI systems that enterprises operate in production, not pilot programmes that never scale.
Our Decade long experience, validated in numbers
Enterprises Projects
Industries
Google Rating
Founded
Enterprise AI Agents
AI Copilots
Multi-Agent Systems
Enterprise Search
RAG Solutions
AI Decision Intelligence
Orchestrator
Enterprise GenAI Opportunity
Most Generative AI initiatives stall between pilot and production.
Enterprises run Generative AI proof-of-concepts that impress in demos but fail to deploy – because the path from a well-prompted LLM to a governed, integrated, production enterprise system is fundamentally an engineering problem, not a prompt engineering problem. XFactr.ai bridges that gap. Our Generative AI consulting practice combines AI engineering, enterprise architecture, and domain expertise – so LLM applications reach production at enterprise scale, with the security, reliability, and integration depth the business requires.
- We engineer, not just advise
- Start with a working proof of value
- Enterprise security and governance built in
Trusted by Leading Enterprises
What we build for enterprise Generative AI.
Eight interconnected Generative AI development capabilities – from foundation model selection through enterprise deployment, integration, and governance.
LLM Development & Integration
Custom Large Language Model implementation, selection, and enterprise integration - GPT-4, Claude, Llama, Gemini, and domain-specific open-source models deployed into production systems.
RAG Architecture & Development
Retrieval-Augmented Generation systems that ground LLM responses in your enterprise knowledge - documents, databases, ERP data, and internal systems. Accurate. Auditable. Current.
AI Copilot Development
Custom enterprise AI copilots for sales, engineering, operations, finance, and customer service - embedded directly into existing workflows and enterprise applications, not separate tools.
Enterprise AI Chatbot Development
Intelligent enterprise chatbots for customer support, internal helpdesks, and technical assistance - grounded in your product catalog, documentation, and knowledge bases, not generic AI responses.
LLM Fine-tuning & Custom Training
Domain-specific LLM fine-tuning on your enterprise data - manufacturing specifications, legal documents, technical manuals, or product catalogs - producing models that understand your business language precisely.
Intelligent Document Processing
AI systems that extract, classify, and reason over scanned PDFs, contracts, invoices, technical drawings, and mixed-format documents - with structured output suitable for downstream enterprise workflows.
Prompt Engineering & Optimization
Systematic prompt engineering and evaluation frameworks that improve LLM output quality, consistency, and reliability across enterprise use cases - measurable, repeatable, and auditable.
Vector Database Implementation
Vector database design and implementation for semantic search, knowledge retrieval, and AI memory systems - enabling LLMs to work accurately with your enterprise's scale of unstructured content.
Generative AI Governance & Security
Responsible AI governance frameworks, data privacy controls, access management, output monitoring, and audit trails - so enterprise GenAI systems meet compliance requirements in regulated industries.
The Production Gap: A Technology Leader's Guide to Genrative AI Development
A practical framework for scoping custom AI development and MLOps engagements, how to evaluate AI development services vendors, what a real technical specification looks like, and the questions to ask before any model training begins.
Delivery Approach
How we deliver Generative AI to production.
XFactr.ai’s Generative AI delivery framework is built around one principle: working software before expanded scope. Every engagement starts with a focused, high-value use case that reaches production before anything else is designed. Senior architects lead every engagement – not handed off to junior teams after a discovery workshop.
IoT-to-model latency on production streaming ML pipelines
Production ML models covering industrial diagnostic use cases
RMSE improvement over statistical baselines on forecasting models
0.8%
False positive rate achieved on production anomaly detection models
Discovery & Use Case Definition
Identify the highest-value Generative AI application for your business. Define measurable success criteria before a line of code is written. Typically, 1-2 weeks.
Architecture & LLM Selection
Select the right foundation model, RAG vs fine-tuning approach, vector database, and integration architecture for your specific enterprise context and data.
Sprint 1 - Working System
A functional Generative AI application demonstrated in the first sprint. Real outputs, not mockups. Stakeholders see value before the engagement is two weeks old.
Enterprise Integration & Security
Connect to ERP, CRM, knowledge bases, and enterprise data systems. Implement AI governance - data privacy, access controls, monitoring, and audit trails.
Production Deployment & Scale
Staged production deployment with performance monitoring, LLM output quality tracking, and continuous optimization. Scale to additional use cases based on proven ROI.
Enterprise AI Agents
AI Agents by Business Function
Purpose-built enterprise AI agents mapped to how every department actually works.
Invoice Processing
Financial Reporting
Reconciliation Agents
Audit Assistants
Expense Validation
Forecasting
Employee Assistants
HR Policy Assistant
Recruitment AI
Resume Screening
Onboarding Agents
Learning Assistants
Sales Copilot
Proposal Generation
CRM Assistant
Opportunity Analysis
Lead Qualification
Customer Intelligence
AI Customer Agents
Omnichannel Support
Ticket Resolution
Knowledge Assistants
Case Summarization
AI Voice Agents
Procurement Agents
Inventory Optimization
Demand Forecasting
Warehouse Intelligence
Supplier Intelligence
Logistics Planning
Production Planning
Maintenance Agents
Digital Work Instructions
Quality Inspection AI
Factory Knowledge Assistants
Shift Intelligence
AI Helpdesk
DevOps Agents
Infrastructure Monitoring
Incident Resolution
AI Operations
Enterprise Automation
Industry Solutions
AI Built for Your Industry
Enterprise Generative AI and Agentic AI solutions tuned to the workflows, systems, and risk profile of your sector.
Manufacturing
- AI production assistants
- Factory copilots
- Quality AI
- Industrial AI agents
Energy & Utilities
- Grid intelligence
- Asset AI
- Energy forecasting
- Field service agents
Buildings & Smart Infrastructure
- Building AI assistants
- Facility intelligence
- Digital twin AI
- Maintenance automation
Construction
- Project AI
- Safety AI
- Document intelligence
- Field operations agents
Healthcare
- Clinical documentation
- Medical AI assistants
- Knowledge agents
- Claims AI
Financial Services
- Compliance AI
- Fraud detection
- Risk intelligence
- Customer AI
Retail & Commerce
- Shopping assistants
- Demand forecasting
- Inventory AI
- Customer analytics
Data Centers
- Infrastructure AI
- Capacity planning
- AIOps agents
- Monitoring AI
Architecture
Enterprise AI Technology Stack
From foundation model to governed production deployment how an enterprise AI agent request actually flows.
Methodology
Our Generative AI Development Approach
AI Strategy
Roadmap, use-case prioritization, and business case.
Enterprise Data Foundation
Governed, connected enterprise data ready for AI.
LLM & Agent Development
Custom models, RAG pipelines, and agent design.
Enterprise Integration
ERP, CRM, document systems, cloud, APIs, identity.
Continuous Optimization
Monitoring, governance, responsible AI, feedback loops.
Scaled Enterprise AI
AI agents operating across every business function.
Why XFactr.ai
An Enterprise AI Partner End to End
Enterprise AI Experts
Deep expertise across AI, data, cloud, engineering, and enterprise systems.
Production-Ready AI
Move from pilots to enterprise-scale AI deployments.
AI + Data + Engineering
One partner for strategy, platforms, applications, and operations.
Secure Enterprise AI
Private LLMs, governance, security, compliance, and responsible AI.
Industry-Focused AI
Solutions tailored for manufacturing, energy, healthcare, finance, retail, and enterprise operations.
Continuous Partnership
From first agent to enterprise-wide autonomous operations.
Client Success
How Enterprises Are Transforming with Generative AI
Global Manufacturer Automates Cross-Department Operations
A global manufacturer needed to reduce manual work across procurement, quality, and maintenance without adding headcount.
XFactr designed a multi-agent enterprise AI platform procurement, quality inspection, and maintenance agents orchestrated together, integrated with existing ERP and MES systems.
What clients say about working with us.
Feedback from the technology and data leaders who commissioned these models.
“XFactr.ai did not just build technology for us. They helped transform how we think and how we grow.”
“An amazing service! The cloud migration project was seamless by making the process much easier.”
“The Tech team is very responsive and they made sure we understood everything along the way.”
FAQ
Generative AI questions from enterprise leaders.
Direct answers – no marketing language.
Generative AI services cover the design, development, and production deployment of AI systems that generate text, code, analysis, reports, or structured data using Large Language Models. This includes RAG architecture, LLM fine-tuning, AI copilot development, enterprise chatbots, and intelligent document processing — all built to enterprise engineering standards.
RAG is an architecture that connects a Large Language Model to your enterprise's own data — documents, databases, ERP records, and internal systems — at query time, so its answers are grounded in current, verifiable information instead of only what the model learned during training. XFactr.ai builds RAG systems using vector databases like Pinecone, Weaviate, and pgvector to keep responses accurate, auditable, and current.
Choose RAG when the priority is grounding answers in frequently changing enterprise data — it's faster to implement and easier to keep current. Choose fine-tuning when the model needs to consistently produce output in a specific format, tone, or domain vocabulary that general-purpose prompting can't reliably reproduce. Many deployments use both together.
XFactr.ai builds Generative AI governance directly into each deployment: data privacy controls, access management, output monitoring, and audit trails, so systems meet compliance requirements in regulated industries — treated as part of the engineering scope from day one, not a review added afterward.
Discovery and use-case definition typically takes 1–2 weeks, with a working system demonstrated in the first development sprint. Full production timelines vary by integration scope — one multi-agent deployment integrated with existing ERP and MES systems went from strategy to production in 18 weeks.
XFactr.ai builds Generative AI and Agentic AI solutions for manufacturing, energy and utilities, buildings and smart infrastructure, construction, healthcare, financial services, retail and commerce, and data centers — tuned to each sector's specific workflows and risk profile.
Resources
Related resources
About XFactr
One Partner for Enterprise AI Transformation
XFactr.ai helps enterprises accelerate AI transformation through Generative AI, Agentic AI, enterprise data platforms, AI engineering, and digital engineering. We design, develop, deploy, and scale secure AI solutions that deliver measurable business outcomes across industries.
Connect With us
Transform Your Enterprise with Generative AI & Agentic AI
Partner with XFactr.ai to build secure, scalable, enterprise-grade AI agents and Generative AI applications that automate operations, empower employees, improve customer experiences, and accelerate digital transformation.