AI Software Development Company
Avenva is an AI software development company that goes beyond chatbots. We build predictive models, intelligent automation, computer vision, and generative AI features that solve concrete business problems, grounded in your data and evaluated before they ship.
In regulated work, the same models drive underwriting, claims triage, and fraud detection. See how we approach fintech and insurance software development specifically.
- You own the code
- Fixed price before work starts
- Reply within one business day
18%
Fraud losses cut by the model (Harborline Insurance)
98%
Client retention
24hr
Average response time
AI development company services, from prototype to production
Not sure what you need yet?
Tell us the problem on a free call. We will suggest what to build first and what can wait.
Book a free callGenerative AI features
LLM-powered search, summarization, drafting, and structured extraction built into your product's actual workflow instead of a chat widget bolted on in the corner.
Predictive & ML models
Forecasting, scoring, and classification models trained and validated on your own operational data, not a generic pretrained model wearing your logo.
Computer vision & document AI
Image recognition, OCR, and document processing pipelines built to handle the messy, inconsistent inputs real businesses actually produce, not clean demo data.
MLOps & evaluation
Model monitoring, evaluation pipelines, and retraining workflows, so accuracy is something you can measure and defend months after launch and not only on demo day.
When to bring in an artificial intelligence app development company
If one of these sounds familiar, that is usually the moment we get the call.
Talk it throughSomeone on your team is the bottleneck
Applications, claims, invoices, or tickets pile up because a person has to read and judge each one. That's usually the clearest sign a model can help, and it's the first thing we'd look at.
You have data nobody's using
Years of orders, tickets, or sensor readings sitting in a database, never turned into a forecast or a score. If the pattern exists in your history, it can usually be modeled.
You want AI in the product, not next to it
A generic chatbot widget is easy to add and easy to ignore. We build AI into the workflow itself (search, drafting, recommendations), where it actually changes how the product gets used.
A no-code tool got you 80% of the way
Zapier, a prompt in a spreadsheet, or an off-the-shelf AI plugin proved the idea works but can't handle your edge cases or scale. That gap is exactly what custom development closes.
How we run this engagement
Feasibility & data audit
Assess whether AI is the right tool and what data supports it.
Prototype
Fast, low-risk proof of concept against real data before full build.
Productionize
Harden the model and pipeline for reliability at real usage volume.
Monitor & retrain
Track model performance and retrain as your data evolves.
How pricing works
Step 1
Free call
Tell us what you need. We ask questions and suggest what to build first.
Step 2
Written scope
You get every feature of the first version listed in writing.
Step 3
Fixed price
One price for that scope, agreed before any work begins.
Step 4
Build and launch
You see progress as we build, then we launch and stay on for support.
Every project is different
One fixed price, agreed up front
We price from the written scope, so you know the full cost before anything is built. Try the calculator for a first estimate.
Included in every project
- Code and accounts in your name
- Testing before launch
- Support after launch
How working with us compares
Who you talk to
Avenva Solutions: The engineers building it
- Typical agency:
- Usually an account manager
- Freelancer:
- One developer
How you pay
Avenva Solutions: A fixed price, in writing, before work starts
- Typical agency:
- Often hourly or open ended
- Freelancer:
- Usually hourly
Who owns the code
Avenva Solutions: You, from day one
- Typical agency:
- Depends on the contract
- Freelancer:
- Depends on the person
Skills on the project
Avenva Solutions: Design, build, testing, launch, and support
- Typical agency:
- A full team
- Freelancer:
- One person's skills
After launch
Avenva Solutions: We stay on for fixes and updates
- Typical agency:
- Often a separate support contract
- Freelancer:
- Depends on their availability
Built on a proven, modern stack
Python
The default language for model training, evaluation, and the ML ecosystem around it.
PyTorch
A flexible framework for building and fine-tuning models beyond what an API alone can do.
Claude API
Frontier reasoning for tasks that need judgment, not only pattern matching.
OpenAI
A second frontier model option, chosen per task instead of by default.
LangChain
Orchestrates multi-step model workflows instead of custom-wiring every call by hand.
Vector DBs
Retrieval that grounds a model's answers in your actual data instead of only its training.
Work we've shipped like this
“The model catches patterns our adjusters were trained to look for, but faster and at real scale. It paid for itself in the first quarter.”
Anita Shah
VP of Claims, Harborline Insurance
Related insights
Things people ask before starting
Can't find what you're looking for? Reach out and we'll answer directly.
How do you decide if AI is actually the right tool for our problem?
We start with a short feasibility pass looking at whether the outcome is predictable or generative from the data you already have. If a rules-based script or a simpler integration solves it more reliably, we'll tell you that instead of building a model you don't need.
Which AI models or providers do you build with?
Mostly Claude and OpenAI for generative work, and PyTorch for custom predictive models, but we pick based on your data sensitivity, latency needs, and budget rather than defaulting to one vendor. We architect so swapping the underlying model later isn't a rebuild.
Will our data be used to train a public model?
No. For most projects we ground the model in your data at query time (retrieval) rather than fine-tuning on it, which keeps your information out of any provider's training set. When fine-tuning does make sense, we use private endpoints and walk through data handling with you before anything starts.
How do you keep the model from making things up?
Grounding it in retrieved facts instead of relying on memory, constraining outputs where correctness matters, and running an evaluation set against known-correct answers before launch. Then we track accuracy in production, not only at demo time.
How long does a typical AI feature take to build?
A working prototype on your real data comes first, usually within a few weeks, so you can see whether it actually works before committing further. Taking it to production with monitoring and retraining depends on the scope of the feature and the systems it connects to, and we set that timeline once the prototype has proven itself.
Do we need our own data science team to maintain this afterward?
No. We hand off documented pipelines and can retain ongoing monitoring and retraining as a support engagement, but everything is built so an in-house engineering team could pick it up without us if that's what you'd rather do.
What should I look for in an AI development company?
Ask how they evaluate accuracy before launch, where your data goes, whether you can switch model providers later, and who owns the code. A good AI development company will also tell you when a rule-based system or a plain database query would do the job better than a model.
Can you build a full artificial intelligence app, not just one feature?
Yes. We build the whole product (web or mobile front end, backend, data pipeline, and the AI layer), so the model is part of a working app rather than a demo that someone else has to wire into production.
