Delivering production-ready LLMs for chatbots, question-answering and more.
I would recommend Winder.AI because they are experts with real-world experience, led by Phil Winder, who is well-respected in the industry. They are quick to respond, quick to scale up and they deliver when you need them to.
We've been developing text-based language models for nearly a decade. Today we offer a range of services to suit your specific needs.
We've worked with hundreds of amazing people, all over the world.
We specialize in developing enterprise-ready LLM solutions.
Unlike larger, more general purpose IT agencies, we specialize in developing AI solutions. We’re more flexible, more pragmatic and better suited to integrate AI into your product.
We combine our bespoke AI solutions with cloud-agnostic or on-premise software engineering to produce production-ready large language models.
We exist to help companies like yours build better products. We collaborate closely with your internal engineering teams to both upskill and deliver pragmatic results.
Winder.AI is a flexible, decentralized, independent AI company that can deliver full-stack solutions. LLMs provide a wide range of experiences via human-like interaction.
Intelligent chatbots, or agents, are able to perform a wide range of roles, including in sales, customer service and HR.
Integrate your internal knowledge bases (through your website, documents and emails, Slack, SharePoint, Salesforce, HubSpot, etc.) to empower your automated agents.
Expose corporate knowledge via streamlined question-answering systems to make your workforce more efficient, e.g. QA platform for Shell.
Deliver next-generation intelligent products by dynamically collating and disseminating information.
Case study
Leveraging predictive analytics and a stand-to-runway modelling approach, Winder.AI and our aviation client improved taxi time predictions to reduced ground delays and improve fuel efficiency.
Case study
Legal AI assistant improves legal coding efficiency by automating data analysis, reducing workload, and accelerating research.
Case study
Interos, a leading supply chain management company, partnered with Winder.AI to enhance their machine learning operations (MLOps). Together, we developed advanced MLOps technologies, including a scalable annotation system, a model deployment suite, AI templates, and a monitoring suite. This collaboration, facilitated by open-source software and Kubernetes deployments, significantly improved Interos’ AI maturity and operational efficiency.
Talk
As visual data becomes increasingly central to enterprise content, traditional retrieval-augmented generation (RAG) systems often fall short when faced with richly visual documents like PDFs filled with charts, diagrams, and infographics. Vision RAG is a cutting-edge pipeline that leverages vision models to generate image embeddings, enabling intelligent indexing and retrieval of visual content.
In this session, you’ll explore the state of the art in visual RAG, see a live demo using open-source tools like VLLM and custom Python components, and learn how to integrate this capability into your own GenAI stack. The presentation will also highlight Helix, our secure GenAI platform, showcasing how Vision RAG fits into a scalable, enterprise-ready solution.
Talk
Building LLM-powered applications is challenging. But the most important challenge is when products are not useful to their users. This presentation is about the different ways you can gather feedback to improve LLM applications. I’ll review the state of the art, offer some practical tips, and share some examples.
Generative AI
The article examines the challenges of moving GenAI from prototypes to production. It highlights issues such as resource constraints, performance monitoring, cost management, and security, and suggests strategies for efficient scaling, robust guardrails, and continuous monitoring to ensure sustainable enterprise-grade deployments.
This page provides answers to our most common questions. If you have a query that isn't covered, please get in touch.
ChatGPT is a product from OpenAI. Under the hood they use large language models (LLM) to generate responses. As an AI agency, we create custom LLMs and generative-AI products for our clients.
Large language models are deep learning models that are pre-trained in a supervised manner, over large text-based datasets. They are used to transform text into a vector (a.k.a. an embedding) for recommendation tasks, or for generation by predicting the next word. Check out our blog series introducing LLMs.
ChatGPT is based on a large language model trained by OpenAI. It works by repeatedly predicting the next word when given a context. The model internalizes knowledge by learning from a wide variety of knowledge graphs like Wikipedia. Check out our talk ChatGPT from Scratch.
Large language models, like those at the heart of ChatGPT can be customized. This process of fine-tuning, allows you to update the machine learning model weights with new knowledge, using your data. Retraining a model from scratch is best avoided because it can incur prohibitive costs. Check out our talk ChatGPT from Scratch.
The team at Winder.AI are ready to collaborate with you on your llm development project. We tailor our AI solutions to meet your unique needs, allowing you to focus on achieving your strategic objectives. Fill out the form below to get started.
