What is Applied AI?
Models like ChatGPT and Claude made it possible for any company to start using AI. But access isn't the hard part anymore. Architecture is. You can't just plug a model into your product and expect it to work. Someone still has to design and build the systems around it. Applied AI ensures your product:
- Has the right architecture and tools
- Works reliably with real users and real data
- An Infrastructure that scales when your business grows
- Stays secure, evaluated, and has proper guardrails
- Keeps working as the model underneath evolve
We Build
We build from first principles - every system designed for clarity, scalability, and long-term impact.
Autonomous systems that handle multi-step tasks without hand-holding.
Instead of users clicking through five screens, an agent does the work. It reasons through the steps, calls the right APIs, uses tools, and gets to the result. We build agents that are actually reliable, with guardrails, evaluation, and the kind of error handling that lets you sleep at night.
For a technical deep dive, check this blog: AI Agents for Tabular Data Processing
RAG (Retrieval-Augmented Generation)
AI that answers questions using your actual data instead of guessing. We build the retrieval pipeline that finds the right documents, feeds them to the model, and makes sure the answers are grounded and accurate.
Knowledge Bases
A structured, maintained source of truth your whole company can rely on. We design the architecture for storing, updating, and serving company knowledge so it stays current and useful.
LLM Wikis
A living knowledge system that AI agents can query and reason over. Unlike static wikis, these update continuously and are built to be read by both people and machines. Learn more about LLM wikis.
Automated extraction, classification, and analysis of unstructured documents.
Contracts, invoices, reports, forms. Every company has a pile of them. We build systems that read through the mess, pull out what matters, and structure it so your product or team can actually use it.
Production-grade vision systems for real-world use.
Quality inspection on a production line. Document scanning. Visual search. Satellite imagery analysis. We build vision pipelines using foundation models or custom approaches.
For machine vision, read here our findings.
Streaming pipelines that act on data as it arrives.
When waiting for a nightly batch job isn't good enough, you need streaming. Data comes in, gets processed, and triggers action, all in real time.
Technical deep dive example: Metaflow in Practice
AI moves fast. New capabilities and use cases emerge all the time. We stay on top of what's happening, learn and evaluate new ways.
If your challenge isn't listed above, reach out. Chances are we've seen something like it or know how to approach it.
Building AI into a SaaS product? Check what we build for SaaS →
With applied AI, we can solve more problems than fit on a page. Here's something we hear often.
- You have a problem you think AI can solve but don't know how to approach it.
- Building it in-house didn't work out the way you planned.
- You need is engineers who actually build, not only consultants who deliver slides.
- The prototype works, but it falls apart when scaling.
- Your engineering team is strong, just not in AI.
- The goal is a system your team can own, not a dependency on a vendor.
What working with us looks like
Problem Definition
We start by understanding your challenge and defining where AI can make sense.
Roadmap
We look at your current stack, what you want to achieve, and the best approaches.
Depending on the maturity of your concept, this phase can kick off with a collaborative workshop or another format suited to your needs.
Proof of Concept
We build a working prototype.
The results tend to be eye-opening: what works, what doesn't, and what matters most. Ideas and priorities might change at this point before we start building the actual product.
Build
We architect and build your solution.
Based on all the base work. Short feedback loops, you are working straight with our engineers, no middle hands.
Delivery & Post
The finished solution is delivered and reviewed together.
We surface new ideas, and help you decide what comes next. No black boxes, no vendor lock-in.
Tools We Use
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OpenAI, Anthropic, open-source models (Llama and others)
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PydanticAI, Vercel AI SDK, LlamaIndex, LangChain, Guardrails AI
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Python, TypeScript, Rust, FastAPI, gRPC
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Metaflow, Bytewax, Argo Workflows
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Logfire, Datalog
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Azure, Modal, Kubernetes
Trusted by saas innovators who shape tomorrow
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