From Texas to the world · AI enablement · Product engineering
Make AI anative layerof your product.
AI consulting and LLM integration for teams that need AI in production. Fixed-price assessment in 2–3 weeks, then senior engineers ship the first use case in your cloud.
30 minutes. You leave with our view of what to do first, whether or not you hire us.
Services
Three ways to work with us. One place to start.
AI Enablement
A fixed-price assessment that ranks your AI use cases, then a pilot that puts the first one in production with evaluations, security review, and your engineers trained to run it.
See what you getProduct Engineering
A lead and one or two senior engineers build your product in two-week iterations, each ending in a demo you can use, with tests, CI/CD, and runbooks included.
See what you getPlatform & Data
An audit of what exists, then the smallest Google Cloud platform that fits, with infrastructure as code, data pipelines with lineage, and a versioned, reversible way to deploy models and prompts.
See what you getWe measure success by how little you need us after launch.
- 2–3 weeks
- To a ranked roadmap you can act on
- 1–3 engineers
- Senior people, no layers between you and the code
- 100% yours
- Code, cloud, and docs in your accounts from day one
How we work
Assess, pilot, scale.
A fixed-scope start, then two-week iterations with a demo each time.
- 01
Assess
2–3 weeks
Week 1: map workflows and data, and talk to the people who would use it. Week 2: test feasibility against your real data and security constraints. By week 3: a ranked roadmap with effort and risk per use case, and what to build first, or a written no.
The assessment - 02
Pilot
typically 4–8 weeks
Every two weeks, a demo in your environment. Evaluations run in CI from the first merge. Monitoring and a runbook are in place before launch.
How we build - 03
Scale
ongoing
Further two-week iterations, only while they earn their keep. Your engineers pair with ours until they run it alone.
Platform work
Why NativeLayer AI
Built to be handed over.
Four things we will not compromise on.
- 01
Senior engineers, not account managers
The people on the call are the people writing the code. Small teams, direct communication.
- 02
Production is the goal
Every build ends with something running, tested, and monitored. The assessment ends with a ranked roadmap, not a slide deck.
- 03
Measured, not guessed
We build evaluation suites for AI features so you know when a change makes things better.
- 04
Your infrastructure, your code
We work inside your Google Cloud and your repositories. You own everything from the first commit.
Fit check
Is NativeLayer AI a fit?
Here is how to tell before either of us spends 30 minutes on a call.
Good fit
- You have a product or internal workflow where AI could remove real work, and you can name the people who would use it.
- You want something running in production in weeks, with your team able to operate it afterwards.
- Your data and systems are on, or can move to, Google Cloud, and security review is part of how you ship.
- You want a direct, senior team rather than a large consultancy with layers.
Not a fit
- You need a large staffing bench or a 24/7 managed service desk.
- You want a demo for a board meeting rather than a feature customers will use.
- You are not able to give engineers access to the systems the work depends on.
Questions
Straight answers.
The things people ask on the first call, answered before it.
All questions, including per serviceHow long does an engagement take?
An assessment runs two to three weeks and ends with a ranked roadmap. A pilot that takes one use case to production typically takes four to eight weeks. Scaling work continues in two-week iterations for as long as it earns its keep.
Who actually does the work?
A lead engineer plus one or two senior engineers. The people on the kickoff call write the code. We do not hand off to a separate delivery team.
How do you price work?
The assessment is fixed scope and fixed price, agreed up front. Pilot and scale work is quoted per milestone or on a time-and-materials basis with a weekly cap, whichever fits your budgeting. No retainer is required to start or to stop.
How do you handle security and data?
Work runs in your cloud project under your identity provider, logging, and access controls. Model and prompt choices are reviewed for data-handling implications before anything reaches production, and every decision is documented so your team can defend it later.
Why not hire in-house or use a larger consultancy?
The engineers on the kickoff call write the code, and your engineers pair with them, so you are not dependent on us afterwards. If you can hire the team you need in the time you have, do that; the assessment will say so.
What do you need from us?
Access to the systems the work depends on, a named person who would use the result, and someone who can decide security questions. Without these the work slows down, and we will tell you.
What happens after handover?
Code, infrastructure, and docs have been yours from day one, so nothing transfers at the end. You can run it yourselves or ask for further two-week iterations. Neither is required.
What if we are not sure AI is the right answer?
Then the assessment is the right first step. Part of its job is to say no to use cases that will not pay off, and we will tell you if a conventional solution is the better fit.
Tell us what you are trying to ship.
A free 30-minute scoping call is enough to tell you whether we can help, what we would do first, and what it would take.
Book a free 30-minute scoping callWe reply within two business days. No deck or RFP needed.