YOUR ENGINEERING TEAM
Senior engineers working inside your business hours, not around them.
METOVA
AI development company.Fast to value, built for production.
AI can get you to a working product in weeks. Making it reliable enough to run every day is where the real work begins. We help you prove the value quickly, and then build it to last: tested, guardrailed, cost-controlled and monitored throughout the project. US-based product leads and architects own delivery, and senior nearshore engineers in Mexico build alongside them, 0 to 2 hours from your time zone.
- 20 years launching production software
- 250M+ downloads delivered
- US-based leads on every team
Get the AI Development guide
How to prove an AI idea in weeks, budget the path to production, and the nine questions to ask any AI development partner.
Metova is a full-service technology partner
Bring us an AI idea, a legacy system or a product ready for its next version. Our strategy, design and engineering teams take it from first proof of concept to a product people rely on every day. We have built production software on both hardware and software since 2006, from mobile apps and websites to sensor networks and connected devices.
(01)
Strategy and AI readiness
Use case selection, success criteria and a technical roadmap, so the first build offers real value.
(02)
Proofs of concept and MVPs
A working build on real data in weeks, with written success criteria, so you can decide on the next phase with confidence.
(03)
UX/UI design
Research-driven interfaces, design systems and accessible experiences that users love
(04)
Web, mobile & platform engineering
Full-stack web, iOS, Android and enterprise platforms built to scale.
(05)
QA & launch
Automated tests, CI/CD and release management, so launches are routine.
(06)
Support and enhancements
Monitoring, optimization and new features after launch, from the same team that built it.
A demo is not a product.
A working demo, accelerated by AI, proves your concept quickly. Production is where most of the cost and risk lives. Keeping results accurate as data changes, costs predictable as usage grows, and being able to explain every output is how we manage AI production throughout the project.
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Quality checks throughout
We define what a good result looks like for your use case, then test against real examples with every change, before anything reaches your users.
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Guardrails and human review.
We set clear limits on what the AI can take in and send out, check its results, and send sensitive or uncertain cases to a person on your team.
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Cost controlled from the start.
We know what each run costs at your expected volume and choose the most efficient model that meets your quality bar. Spending limits and timeouts keep costs predictable.
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Monitored after launch.
We track every request, response, model, response time and cost, so we can spot changes in quality early and fix them before your users are affected.
WHAT YOU CAN FIND IN THE GUIDE
Make the right AI decisions from the start.
Our AI development guide is a practical look at what it takes to move AI from proof of concept to production: what to build first, how to budget, and what to expect from any partner, including us.
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Why AI features slip after launch
How real usage exposes issues a demo won’t show.
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Quality checks that hold up
How to define a good result and test against real examples on every change.
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Know your costs before launch
How to estimate cost per request at your expected volume and set spending limits.
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Stable models without surprises
Why locking model versions and testing every change keeps results consistent.
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Built-in safeguards
Limits, backups and human review that keep AI reliable in production.
20 years
building production software, all of it
250M+
downloads across every product we have shipped
$1B+
in revenue generated for our clients
These are company numbers across twenty years of software, not AI numbers. Metova builds production software for US companies from offices in Bentonville, Arkansas and Guadalajara, Mexico.
Built for production, proven at scale.
SPORTS TECH · REAL-TIME DATA
Barwis
Real-time biometric data from four wearable platforms, feeding an adaptive programming engine that adjusts when an athlete’s recovery signals fatigue.
Read the case study (opens in a new tab)
ENTERPRISE · SAAS PLATFORM
Acoustic
16 engineers across four disciplines on an enterprise marketing and analytics platform.
Read the case study (opens in a new tab)
FINTECH · MOBILE
MyBambu
Mobile banking for the underserved, shipped for iOS and Android on FIS Global rails.
Read the case study (opens in a new tab)WHERE THE WORK HAPPENS
Bentonville, Arkansas. And Guadalajara, MX.
Our headquarters in Northwest Arkansas, puts US-based product leads and architects in your time zone, while the senior engineers building alongside them are in Guadalajara, MX, 0-2 hours within your time zone. A hybrid delivery team approach that optimizes production and ensures accountability.
Bentonville, AR.
Headquarters, product leads and architects
Guadalajara, MX.
Senior engineering
0 to 2 hours.
Time difference from anywhere in the continental US
Full custom builds
One integrated team, from concept to launch. You own the product while we own the delivery plan.
Embedded expert teams
Senior engineers join your team, still reviewed and led by US-based seniors.
LED BY METOVA LEADERSHIP
- Product Owner
- Senior Architect
- Project Manager
- QA Lead
US-based, accountable for the outcome.
THE RESULT
Your product.One accountable and consistent delivery team.
Project Engagement Process
(01)
Discovery call.
Our architect and project lead will discuss the current state of your product, your end goals, and we will define the gap to determine your project's scope.
(02)
Scoped plan.
We will review any available documentation and consider our discussions to create a proposal outlining the suggested initial scope of work, budget, team composition, and timeline. We will deliver the proposal and open the conversation to finetune the commitment.
(03)
Project Kickoff.
We begin onboarding and create a standup cadence and a direct communication line through Slack.
You may be wondering
How do you scope an AI project?
We start by identifying what you need: a proof of concept, a pilot or a production product. Then we agree on written success criteria, the capabilities that matter most and where the system will run in production. New ideas go into a backlog with an estimate, so scope stays clear.
What does an AI build cost?
We budget in two phases. A fixed, small proof of concept with clear exit criteria comes first. The production budget is sized after you see real results and covers the work that makes it reliable: code review, QA, infrastructure and release management.
Which models do you use?
We start with the smallest model that clears the quality bar for your use case. We design so models can be swapped without a rebuild, pin versions and test every change, and give your users a few approved settings instead of every option.
How do you keep it from drifting or getting expensive?
We log every input, output, model, response time and cost, and test quality against real examples on every change. We set cost per run targets, limits and timeouts before launch, so quality and spend stay visible and predictable.
Do you work with our existing data and engineering team?
Yes. We connect to your real data and services from the first build and work on your target environment. We can own the full build or embed senior engineers in your team, and your developers join early so they shape the system they will support.
What happens after launch?
We plan the rollout with training, support and a short stabilization window. After that, the same team stays on for monitoring, optimization and new features, with regression testing on every release.
AI PRODUCT DEVELOPMENT · US-LED · PRODUCTION READY
Build AI your business can rely on
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