Insights

Ideas on applied AI

Field notes from the studio — how we ship AI that holds up in production, and the decisions that separate a demo from a dependable product.

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Why we write

What we learn in production

Every model we ship teaches us something the papers don't — how RAG behaves under real load, where agents drift, what makes an eval trustworthy. We write it down so you don't have to relearn it the hard way.

No thought-leadership fluff. Just the decisions, trade-offs and hard-won details that separate a demo from a dependable product.

Generative AI

RAG in production: beyond the demo

Retrieval-augmented generation is easy to prototype and hard to productionize. Here's what actually matters when you take RAG live.

Muhammad DayyanJune 18, 20267 min read

AI Agents

When to use AI agents (and when not to)

Agents are powerful and easy to over-apply. A practical framework for deciding when autonomy earns its keep.

Marcus ReidMay 29, 20266 min read

Strategy

AI that earns its place

Not every problem needs a model. How we help teams pick the AI use cases that actually move the numbers.

Muhammad DayyanMay 12, 20265 min read

Engineering

MLOps without the buzzwords

Models drift, data changes, and yesterday's accuracy is no guarantee. What it really takes to keep AI working in production.

Marcus ReidApril 24, 20266 min read

Strategy

Designing trust into AI products

The difference between AI people use and AI they abandon is rarely the model. It's the experience around it.

Ayesha KhanApril 3, 20265 min read

Generative AI

Evals: turning AI quality into a number you can track

Vibes don't ship. If you can't score your AI system, you can't tell whether a prompt tweak helped or quietly broke three other things. Here's how we build evals that hold up.

Muhammad DayyanJune 24, 20268 min read

Engineering

What LLM inference actually costs (and how to cut it)

The token price on the pricing page is the smallest part of the bill. Here's where LLM cost actually comes from in production, and the levers that move it without hurting quality.

Muhammad DayyanJune 26, 20268 min read

AI Agents

Guardrails for AI agents that take real actions

An agent that only writes text is low-stakes. An agent that can send emails, move money or change records is a different animal. Here's how we make action-taking agents safe enough to trust.

Muhammad DayyanJune 30, 20268 min read

Have an AI problem worth solving well?

Tell us the outcome you're chasing. We'll bring the AI, engineering and design to get there.

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