Bespoke AI Development & Expert Team Augmentation
We build custom AI solutions tailored to your business and augment your team with the expertise needed to deliver results
Production AI Systems
We operationalize complex AI, ensuring scalable, production-ready solutions that deliver real-world impact.
Generative AI & Agents
Authored bestselling guides on enterprise GenAI, building advanced LLM applications and intelligent agents.
Measurable Business Value
Our solutions drive tangible ROI, with proven impact on marketing efficiency and significant fraud loss prevention.
Deep Technical Authority
International authority, bridging cutting-edge research with battle-tested industry implementation.
How We Partner With Your Business
Bespoke AI Development
Custom AI solutions designed specifically for your business challenges, built by expert developers who integrate seamlessly with your team.
- Custom Solution Architecture
- Tailored LLM and ML Applications
- Seamless System Integration
- Expert Team Augmentation
Why Bespoke AI Solutions Deliver Better Results
Perfect Fit Solutions
Off-the-shelf AI tools force you to adapt your processes. We build solutions that fit exactly how your business works, maximizing efficiency and adoption.
Enterprise Security & Control
Generic AI platforms mean shared infrastructure and limited control. Custom solutions give you complete ownership, security, and compliance control.
Deep Integration
SaaS solutions often create data silos. Our bespoke systems integrate seamlessly with your existing infrastructure, creating unified workflows.
Competitive Advantage
Everyone else uses the same generic tools. Custom AI solutions become your competitive moat, delivering unique capabilities competitors can't replicate.
Technical Expertise You Can Trust
Our bespoke solutions are backed by deep technical knowledge documented in industry-leading publications
Generative AI with LangChain (2nd edition)
Build production ready LLM applications and advanced agents using Python and LangGraph
A practical guide to leveraging LangChain and LangGraph for GenAI implementation, with real-world examples ranging from customer support to data analysis.
Machine Learning for Time Series
Forecast, predict, and detect anomalies with state-of-the-art machine learning methods
Use Python to forecast, predict, and detect anomalies with state-of-the-art machine learning methods.
Artificial Intelligence with Python Cookbook
Proven recipes for applying AI algorithms and deep learning techniques
Proven recipes for applying AI algorithms and deep learning techniques using TensorFlow and PyTorch.
The Open-Source AI Advantage
Chelsea AI Ventures has deep expertise implementing system with both commercial and open-source LLMs. For many clients, particularly SMEs, open-source models like Meta's Llama can offer significant advantages in cost, customization, and control. Our team specializes in deploying these cutting-edge models tailored to your specific business needs.
Cost Effectiveness
Open-source LLMs can significantly reduce operational costs compared to commercial API-based models. For many applications, you can save 70-90% on inference costs while maintaining comparable performance.
Customization & Control
Fine-tune models to your specific domain and use cases, creating AI that truly understands your business language. Maintain full control over your data without sharing it with third-party API providers.
Data Privacy & Compliance
Deploy models on-premises or in your private cloud, ensuring sensitive data never leaves your secure environment. Ideal for industries with strict regulatory requirements like healthcare, finance, and legal.
Performance Optimization
We specialize in quantization and optimization techniques that make large models run efficiently on standard hardware. Our expertise ensures you get maximum performance without requiring specialized infrastructure.
Our Open-Source LLM Expertise
Our team has implemented open-source models across diverse use cases, from customer service chatbots to specialized document analysis systems. Chelsea AI's founder is the author of "Generative AI with LangChain," an Amazon bestseller on implementing production-ready LLM applications.
Implementation Capabilities
- Local deployment of Llama 2 & 3 models with optimal resource utilization
- Custom fine-tuning for domain-specific knowledge and terminology
- Integration with existing workflows and enterprise systems
- RAG pipelines for grounding responses in your business data
- Multi-modal capabilities combining text and image processing
Business Outcomes
- Reduced operational costs (70-90% compared to API services)
- Enhanced data security with full control over your information
- Customized AI that speaks your industry's language
- Faster response times without API latency
- Future-proof solutions as open-source models continue to advance
Chelsea AI helped us implement a fine-tuned Llama model that understands our industry terminology and handles our customer queries with remarkable accuracy. By hosting it on our own infrastructure, we've reduced costs by 85% compared to commercial API solutions.— Technical Director, FinTech SME
Collaboration Models
We structure our collaboration to address the real challenges technical leaders face: budget approval, risk management, and stakeholder confidence.
"We think this could work, but need proof before we can get budget approval."
Validation Partnership
Prove it works before you invest
A self-contained proof-of-concept that validates your AI initiative's feasibility without internal dependencies or large commitments.
Real Example:
One client couldn't use internal data for the PoC due to IT security policies - we built on our infrastructure instead, delivering validation in 4 weeks without any internal IT involvement.
Best for: When you need proof an AI solution will work within your constraints before seeking larger budget approval.
"We want you as the brain of the project - doing architecture and guiding our team."
Advisory Collaboration
We design, you build, we guide
A collaborative approach where we provide technical architecture and ongoing guidance while your team builds, retaining full ownership.
Real Example:
A client's technical team preferred us as 'systems engineers' - we designed the architecture, provided ongoing checks, and guided implementation while they retained full ownership and built internal expertise.
Best for: Organizations wanting to build internal AI capabilities while ensuring technical success and mitigating risk.
"The timeline has to work with the budget. We need something tangible with clear milestones."
Collaborative Implementation
Shared risk, shared success
Full development with payments tied to demonstrated progress, allowing you to validate value at each stage before continuing.
Real Example:
An organization had tried similar automation in 2012 that failed on different devices. We structured milestones specifically around their constraints, allowing them to validate each component before proceeding.
Best for: Larger projects where you need to demonstrate progress incrementally to stakeholders and de-risk a significant investment.
Not sure which approach fits your situation?
Every organization has different constraints. Let's discuss your preferred collaboration approach.
Discuss Your CollaborationReady to build AI solutions that fit your business perfectly?
Let's discuss how our team can augment yours to deliver the custom AI capabilities you need.
Start Your Project