From strategy to production, we design, build and ship Generative AI applications, RAG systems and autonomous agents on GPT, Claude, Gemini and open models — grounded in your own data and built to earn their place in the business.
LLM Integration
RAG & Vector Search
AI Agents
Custom AI Apps
The technology ecosystem we build on
Generative AI is more than a chatbot. It reads your documents and data, writes and summarizes content, reasons across systems, and takes multi-step actions through agents — wrapped in interfaces your customers and teams actually use. It is also a fast-moving market: generative AI spending is projected to reach roughly $1.3 trillion by 2032 (Bloomberg Intelligence, 2023).
The value isn't the model; it's what you connect it to. So we ground large language models in your own knowledge through retrieval and data pipelines, add guardrails and evaluation so outputs stay accurate, and ship it as a real product — not a demo. If a workflow is core to how you win customers or run operations, that is a strong candidate for a generative AI build.
There is no single way to build with generative AI, and choosing the wrong one wastes budget. For focused tasks, careful prompt engineering on a leading model is often enough. When answers must reflect your own knowledge, retrieval-augmented generation pulls the right context at query time, so the model stays current without costly retraining. When tone, format or a narrow domain matter, fine-tuning adapts a model to your data. And when work spans several steps and systems, agents plan, call tools and act. In short, we match the approach to the problem rather than the hype, and combine them where it helps.
Shipping generative AI responsibly is where most projects stall. So we treat evaluation as part of the build — measuring accuracy, relevance, cost and latency against real examples before anything reaches your users. Guardrails constrain what the system can say and do, retrieval keeps it grounded in trusted sources, and human review sits wherever the stakes are high. Security and compliance are designed in from day one: your data, prompts, models and code stay under your control, deployed in the environment your policies require.
Because the value comes from what the model connects to, we engineer for your existing stack — your apps, databases, CRMs and internal tools — so AI amplifies the systems you already run instead of adding another silo. You own everything we build, and we hand over clean, documented code and infrastructure so your team can extend it long after launch.
Most engagements begin small on purpose. A tightly-scoped proof of concept — built on your real data, not a sandbox — shows what quality, cost and effort actually look like for your use case, so the decision to scale rests on evidence rather than a vendor promise. From there, the path to production becomes a roadmap you can budget against: what to build next, what it should return, and how we'll measure whether it worked.
Not sure where to start? A short strategy engagement maps the highest-ROI use cases before a line of code is written.
From strategy and experimentation to production-ready AI products — one team from first workshop to deployment.
Identify high-value use cases, assess feasibility and data readiness, and build a costed roadmap for AI adoption — before anyone writes code.
Explore service 02Bespoke AI apps engineered around your data and workflows, built on GPT, Claude, Llama and open models. From internal productivity tools to customer-facing products, we design, build and ship the full application — not just the model call.
Explore service → 03Retrieval-augmented answers grounded in your own documents, so responses stay accurate and current. We build the ingestion, embedding and search layer that lets teams query policies, manuals and records in plain language.
Explore service → 04Autonomous, tool-using agents that complete multi-step tasks across your systems — not just chat. They plan, call your APIs and hand off to people when judgment is needed, with logging and controls throughout.
Explore service → 05Conversational assistants and in-product copilots that support customers and speed up real work. Grounded in your knowledge base, they answer accurately, escalate gracefully and improve with every interaction.
Explore service → 06Fine-tuning, prompt engineering, evaluation and integration into your existing product and stack. We benchmark models against your own test cases so you ship on quality, cost and latency you can actually measure.
Explore service →A few of the generative AI systems we design, build and ship into production. If you can describe the workflow, the data behind it and the outcome you want, it can almost certainly be built — and we've shipped variations of most of these before.
We don't build AI because it's trending. We build it to move a number that matters — then we measure it. Every engagement starts from the outcome you're after and works backward to the smallest system that delivers it.
Every build is adapted to the data, compliance and workflows of your sector — because a healthcare assistant and a retail content engine share a foundation but answer to very different rules. We bring patterns that work and tailor them to how your industry actually operates.
A growing catalog meant thousands of product descriptions, SEO pages and image variations written by hand — slow to publish and expensive to maintain. Every day of delay meant new products sitting unpublished while competitors listed theirs.
A generative AI system that drafts product descriptions, marketing copy and SEO content grounded in real product data, with human review built into the workflow. It plugs into the existing catalog and content process, producing on-brand copy in multiple formats from a single source of truth.
The team ships new products faster with a fraction of the manual writing, and content stays consistent across the catalog. Writers moved from producing copy from scratch to reviewing and refining it — and the same system now scales to new categories on demand.
A transparent, agile path that de-risks AI before you scale it — so you see working software early and commit budget with confidence.
Understand goals, data and the highest-ROI use cases. We interview stakeholders and audit your data so we build the right thing first.
Define the architecture, models and user experience, choosing between RAG, fine-tuning and agents to fit the problem.
Develop, integrate and ground the AI in your data. Working in short iterations, we put a usable version in your hands early.
Test accuracy, safety, cost and performance against real examples, tuning until the system is ready for production.
Ship to production, monitor quality in the wild, and keep retraining and improving as usage and needs grow.
We're not an AI lab running experiments on your budget, and we're not a staffing shop renting out seats. We're a product-engineering team that has shipped 500+ products over 12+ years — now applying that same discipline to generative AI, so what we build is reliable, secure and genuinely ready for production.
Tell us the outcome you want. We'll map the fastest path to a working, production-ready generative AI solution — and where it creates measurable value.
Tell us about your project and our team replies within 24 hours with a clear scope and estimate — no obligation.
