AI tools built around what your team actually does
We build computer vision tools, internal interfaces, and review AI plans — always with a candid account of where the technology holds and where it does not.
Three focused services
Each engagement is scoped to a concrete deliverable. We do not sell vague advisory — we show up with a defined scope, honest timelines, and a clear account of what the result will and will not do.
Computer Vision Tooling for Inspection
A targeted vision-based tool for visual inspection in industrial, logistics, or hospitality contexts — counting items, flagging defects, or identifying unusual conditions in image feeds. We begin with a careful conversation about what the operator currently does and where they want to stay in control.
- Dataset collection and honest labeling
- Performance measured and reported candidly
- Human operator kept firmly in the loop
- Eight to ten week implementation
Conversational Interface for Internal Use
A constrained chat interface for internal teams — built on top of your documents, with retrieval and citation, so users can see where answers come from. We define what the interface will and will not respond to, and build refusal behaviors carefully.
- Document retrieval with visible citations
- Explicit limits defined and documented
- Quarterly review sessions in year one
- Users know what to expect and why
Two-Hour Architecture Review
A two-hour review session with your technical leadership, focused on a planned or in-progress AI project. We read your architecture documents in advance, ask candid questions, and follow up with a brief written note of the points we believe deserve attention.
- Architecture documents reviewed before session
- Candid questions and honest concerns raised
- Written follow-up note included
- In person or by video, your choice
How we approach the work
Most AI projects run into trouble not because the technology is wrong but because the expectations were not shaped carefully. We try to set those expectations before any code is written.
Candid performance reporting
We measure what the model does, report the numbers without rounding them up, and note the conditions under which it fails. You make decisions based on that.
Human operators stay in control
Every tool we build is designed with a human in the loop at the decision point that matters. We do not design for full automation unless the client has thought through what that means.
Documented limits
Each delivered system includes written documentation of what it was built to handle and what it should not be used for. That document stays with the client.
Scoped, not open-ended
We define the scope before starting. The engagement covers what is agreed. Changes to scope are discussed and priced separately, not absorbed silently.
Context-first conversations
Before recommending a tool, we ask what the operator currently does, what they find difficult, and what they prefer to keep doing themselves. The answer shapes the build.
Data handled carefully
Client documents and image datasets are used only for the agreed purpose. We do not train shared models with proprietary client data without explicit written agreement.
Have a project in mind? Let's look at it together.
Send us a brief description of what you're working on. We'll read it, ask a few questions, and tell you whether and how we can help. No pitch deck required.
Questions we get asked
Do you work with teams that have no prior AI experience?
How long does a computer vision project take?
What does the conversational interface use as its source material?
What is included in the architecture review?
Are the prices fixed or do they vary?
How do you handle client data?
Our office in Dubai
Sheikh Zayed Road, Boulevard Plaza Tower 2, Suite 1709, Dubai, UAE