:: AI services / AI software development
An AI software development company that ships to production
We build custom AI software: the models, the data pipelines, the app around them and the monitoring that keeps them honest once real users arrive. One team, from first prototype to version two.
Custom AI, not templates
Built in your cloud
Evaluated before launch
:: What we do
Custom AI development services
Every project is different, but most of what we build falls into one of these groups.
01
AI features in existing products
Search, summaries, recommendations, smart forms and assistants added to software you already run, without a rewrite.
02
New AI-first products
SaaS tools and platforms where AI is the core of the product. We help shape the MVP, then build and scale it.
03
Internal AI tools
Assistants for sales, support, finance and operations teams that work on your own documents and systems.
04
Data pipelines and APIs
The plumbing that gets clean, current data to your models and returns results to the apps that need them.
05
Model selection and tuning
We test several models on your task and pick on accuracy, speed and cost. Fine-tuning only when it clearly beats a well-built prompt.
06
Monitoring and support
Dashboards, alerts and regular evaluation runs so you know when quality slips and why.
:: Examples
What custom AI software looks like in practice
Each of these started as a slow, manual job inside a real kind of business. Read the blueprints to see how the software is put together, what it connects to and how it is tested.
Documents
Reading and checking paperwork
Loan files, claims and invoices read by AI, checked against rules and passed on as clean data, with a person reviewing exceptions.
Read the blueprint
Insurance
Claims triage
New claims sorted by type and urgency, missing information requested automatically and simple claims fast-tracked.
Read the blueprint
Hiring
Candidate screening
CVs matched against role requirements with the reasons shown, so recruiters spend their time on the right people.
Read the blueprint
Manufacturing
Visual quality inspection
Cameras on the line flag defects in moulded parts, with every decision stored for audits.
Read the blueprint
Operations
Predictive maintenance
Sensor and work-order history used to predict failures and plan repairs before equipment breaks.
Read the blueprint
Knowledge
Internal search and answers
Staff ask questions in plain language and get answers from company documents, with links to the source.
Read the blueprint
:: Step by step
How custom AI software gets built, from idea to production
AI software is ordinary software with one unpredictable part. Most of the work is making that part measurable, safe and cheap to run. This is the order we work in.
01
Define the task and the measure of success
Write down what the software should do, who uses it and how you will know it works: accuracy, time saved, cost per task. Without a measure, nobody can say if version two is better.
02
Check the data
Look at the documents, records or images the AI will work with. How much is there, how clean is it, who may see it, and where must it stay?
03
Build a test set
Collect real examples with the right answers. This set decides which model to use, catches regressions and tells you when the software is ready.
04
Prototype and compare models
Try a few models and approaches on the test set in two to four weeks. Choose on accuracy, speed and running cost, not on headlines.
05
Build the product around the model
User interface, integrations, permissions, error handling and a way for people to correct the AI. This is where most of the build time goes.
06
Harden for production
Load testing, security review, cost limits, fallbacks for when a model is slow or down, and logging for every decision.
07
Launch, monitor and improve
Release to a small group first, track quality and cost on a dashboard, and rerun the test set before every change.
:: How it works
How we build AI software
AI projects fail when quality is judged by demo. We judge it by tests.
01
Define success
We agree on the tasks, the data and the tests the system must pass before anyone writes code.
02
Prototype
A rough working version in two to four weeks, tested on real examples from your business.
03
Build
Production code in weekly sprints: security, access control, logging, error handling and a proper UI.
04
Launch and improve
Staged rollout, live monitoring and a monthly review of failures, costs and new use cases.
:: Cost and timeline
How much does custom AI development cost?
Typical prices for our projects, based on a senior team at $25 to $35 an hour. After a short call you get a written estimate with scope, timeline and running costs.
Prototype
$5k – $15k
2 to 4 weeks
One task, tested on your real data, with a simple interface and a clear read on accuracy and running cost.
Production release
$20k – $60k
2 to 4 months
A secure, integrated application for real users, with permissions, monitoring, evaluation and support.
AI product or platform
$60k – $150k+
4 to 9 months
An AI-first product or a platform serving several teams, with multiple models, integrations and MLOps.
What it costs to run
Running costs are model usage plus hosting, and depend on volume and which model each task needs. Most business applications run for a few hundred to a few thousand dollars a month. We estimate this before the build and set limits so it stays there.
What moves the price
How many systems it must connect to
Quality and volume of your data
Security, compliance and hosting rules
Number of users, roles and languages
Whether a custom or fine-tuned model is needed
:: Build or buy
When custom AI software is worth building
Off-the-shelf AI tools are often the right answer. We will tell you when one fits, and when building your own pays off.
Build custom when
The task is core to how you make money
It must work inside your own systems and data
Data must stay in your cloud or region
Per-seat tool pricing gets expensive at your scale
You need to own the logic, prompts and models
No product on the market fits your process
Buy a tool instead when
A standard tool already does 90% of the job
The process is generic, like meeting notes
You need it running this week
Nobody will own it after launch
The volume is too low to justify a build
:: Why Sterling
Why companies choose us as their AI development company
Senior engineers who have shipped 350+ projects since 2019
One team covers AI, backend, web and mobile, so nothing gets lost in handover
Your data stays in your cloud or your Salesforce org
Model-agnostic: we switch models when a better one appears
4.9 average rating on Clutch
:: Tools we use
Python
FastAPI
Node.js
React
PostgreSQL + pgvector
OpenAI
Claude
Gemini
Llama
AWS
Azure
Google Cloud
Docker
Kubernetes
4.9
Average rating on Clutch · 350+ projects since 2019
:: Questions
Questions about AI software development
How much does custom AI development cost?
How long does it take to build AI software?
Will you train our own model?
Who owns the code and the model?
Can you work with our in-house developers?
What does an AI software development company do?
What is the process for custom AI development?
Which AI models and tools do you use?
Can the AI software run in our own cloud?
How do you test AI software before launch?
What does custom AI software cost to run each month?
:: Related AI services
Other ways we can help
Send us your brief. We’ll help turn it into reality
A senior engineer replies within one business day with questions or a first plan: approach, team, timeline and estimate.