AI Software Development
Ship AI features that hold up in production, not just in a demo.
AI software development is the engineering of applications where models — usually large language models — do real work inside the product: answering from your own data, running agents, or automating decisions. Asauvia builds these for teams who need AI that is measured, monitored and affordable in production, not a prototype that only works in a demo.
- What it is
- AI software development services
- Engagement models
- Fixed scope, dedicated team, or time and materials
- Typical stack
- Python, TypeScript, OpenAI & Anthropic APIs, Open-weight models, Vector databases, PostgreSQL
- Delivered from
- India, working India Standard Time for international teams
When do teams need
AI Software Development?
- An AI prototype impressed in a demo but gives unreliable answers on real data.
- Model costs grow faster than usage, with no visibility into why.
- Nobody can say whether the AI is actually getting better or worse after a change.
- The AI feature lives outside the product and doesn't use your own data or systems.
What Asauvia delivers
for AI Software Development.
We design and build applications that use large language models and other AI systems as working parts of the product — retrieval, agents, chatbots, and model integration included — engineered for the accuracy and cost constraints of a real business.
- Model and architecture selection for the actual task, not the trend
- Retrieval-augmented generation (RAG) pipelines over your own data
- AI agents and context-aware chatbots wired into your systems
- Evaluation harnesses so quality is measured, not assumed
- Production hardening: rate limits, fallbacks, and cost monitoring
Where AI Software Development
makes a difference.
Answering from your own documents
A retrieval pipeline over manuals, policies, or a knowledge base, so answers cite your sources instead of guessing.
Context-aware support and internal chatbots
Assistants that can look things up in your systems and hand off to a person when a question needs one.
AI agents for multi-step tasks
Agents that gather information, call your APIs, and complete a defined workflow, with checkpoints where a human approves.
Adding AI to an existing product
Summaries, classification, extraction, or search added to an application you already run, without rebuilding it.
How the project
moves, stage by stage.
- 01
Discover
Scope the real problem and constraints on a short call.
- 02
Design
Architecture and plan, reviewed with you before anything is built.
- 03
Build
Iterative delivery against a shared backlog, not a black box.
- 04
Validate
Testing and review gates before anything ships.
- 05
Launch
Deploy with monitoring and rollback in place from day one.
- 06
Improve
Measure against the original goal and keep iterating.
AI Software Development:
what buyers ask.
Should we use RAG or fine-tune a model?
Most business use cases start with retrieval-augmented generation (RAG): it keeps answers grounded in your current data and is cheaper to update. Fine-tuning makes sense for consistent style, format, or a narrow task where retrieval alone is not enough. We usually test RAG first and fine-tune only when evaluation shows it is needed.
How do you know the AI is giving good answers?
We build an evaluation set from real examples of your questions and expected answers, and run it on every change. That turns 'it seems better' into a measured result, and it catches regressions before users do.
Can you work with our existing product and data?
Yes. Most of this work is integrating AI into systems you already run — your database, your APIs, your documents — rather than building a separate tool beside them.
Which models do you use?
Whichever fits the task, cost, and data requirements: hosted models from providers such as OpenAI and Anthropic, or open-weight models you can run in your own environment when data must stay in-house.
How do you keep model costs under control?
By measuring cost per request from the start, caching where answers repeat, routing simple requests to smaller models, and setting limits and alerts so spend never surprises you.
Often paired
with AI Software Development.
AI Workflow Automation
Take repetitive work off your team without losing control of it.
Data Engineering & Integration
Make your systems' data usable in one place.
Custom Software Development
Software shaped around how your business actually works.
Let's solve
something together.
Tell us what you're building, improving, or automating. We'll come back with a plan, not a pitch.
NDA before any scoping conversation