Your AI works in demos. It fails with real users. You're not sure why.

Your AI should drive results, not just impress stakeholders. We help you build, measure, and ship AI that works.

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Agents

AI systems that think, decide, and act.

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I found a new inquiry from Acme Corp. They're asking about the Q4 project timeline. I'll draft a response confirming our availability.
Checked team calendar for Q4 availability
alice@acme.com
Q4 Project RFP

Hi Alice,


Thanks for reaching out. We have availability to start the Q4 project in mid-October. I've attached our updated rate card.


Gang

Evals

Find where AI fails before users do.

customer_support_agent
6.8s
classify_intent
850ms
fetch_user_context
1.5s
search_knowledge_base
1.2s
generate_resolution_plan
2.1s
draft_response
1.8s
RAG

Make AI smarter with your own data.

Based on your Q3 performance data and the latest market research, revenue increased 23% quarter-over-quarter. The APAC region showed the strongest growth at 31%, driven primarily by the enterprise segment.


I recommend focusing expansion efforts on Singapore and Tokyo markets, where competitor analysis shows significant opportunity.

Why AI projects get stuck.

Every fix feels like a guess.

Tweak prompts. Try a different model. Something feels better, so you ship it. A week later, same complaints, or new ones. Hard to tell if the change actually helped.

Traditional testing doesn't work here.

Same input, different output every time. Unit tests break. Without a way to systematically evaluate performance, there's no baseline to improve against.

Sometimes the problem isn't the AI, it's what it's solving.

The system works as designed. But users still aren't getting value. When that happens, the issue usually isn't technical. The AI is solving the wrong problem.

Here's how we help.

Clarify the real problem.

We dig into what users are actually trying to accomplish—not what's assumed. The best AI feature is useless if it solves the wrong problem.

Prototype something real.

No slide decks. A working prototype within days, so you can validate with actual users before committing to full implementation.

Set up measurement from day one.

Systematic evaluation: which queries fail, what patterns cause problems, whether changes actually help. Every improvement has data behind it.

Within days, not weeks.

What we build.

AI agents

Agents that take action on behalf of users. We design the architecture, build working prototypes, and set up evaluation to track performance.

Retrieval solutions

RAG knowledge bases, document Q&A, semantic search. We help you build high performing and accurate retrieval systems.

AI internal tools

Custom AI tools for specific workflows. Built for your team's actual needs, not generic features.

Evaluation systems

We set up the infrastructure so your team can measure AI performance, identify failure patterns, and validate improvements.

Who we work with.

Companies adding AI to existing products.

You know you need AI capabilities. Your competitors have them. But you've seen too many projects fail, and you don't want to waste months building the wrong thing.

Teams that have AI but can't improve it.

Your AI works... sometimes. You've made changes, but you can't tell if they're helping. You need a systematic way to diagnose issues and measure improvements.

Startups building AI products.

You've shipped an AI feature. It's not performing like you expected. Users aren't engaging the way you hoped. You're not sure if it's a product problem or a technical problem—or both.

We're probably not the right fit if:

  • •You need a full engineering team to build and maintain large-scale systems
  • •You're looking for deep ML research or custom model training
  • •You want someone to build something and disappear without knowledge transfer

Who's behind this

Gang, Founder
Gang
Chief Product Builder

We're a small team that helps companies build AI that actually delivers results.

A bit about us

Years of building products in startups, from design to code. We've seen this pattern too many times: teams ship impressive AI demos, real users show up, and suddenly nothing works like it should.

Why we started this

Most AI consultants are either product people who can't code, or engineers who don't get business context. We do both. Product thinking to find the right problem. Hands-on implementation to solve it. The fix usually isn't more engineering. It's asking the right questions and having a way to measure what's working.

How we work

We get into your codebase, understand your users, and build working prototypes fast. We document everything and train your team along the way. When we're done, you can run and improve the system without us.

Your AI can work better.

Let's figure out what's broken and how to fix it.

Frequently Asked Questions

Engineers are great at building. But the problem usually isn't building—it's knowing what to build and whether it's working. We bring product thinking and evaluation methodology that most engineers haven't developed. Plus, we've seen these patterns across multiple companies, not just one codebase.