Services / AI Development
AI development that ships to production.
Agents, document intelligence, voice AI and automation, built into the systems you already run and measured against real workflows.
AI development services. Twelve ways we build with AI. The first seven are backed by delivered work.
Document intelligence
Extraction and classification that sends only the exceptions to people.
Explore →Voice AI agents
Live call agents for scheduling, verification and follow-up, with a human escalation path.
Explore →AI workflow automation
AI extraction paired with deterministic business rules, for consistent output.
Explore →AI agents & agentic AI
Agents that retrieve, reason and act across systems, with approval before high-stakes actions.
Explore →AI chatbots
Support and booking assistants that answer from live data, around the clock.
Explore →AI SaaS development
AI-powered software products, from first lovable release to scale.
Explore →AI integration & support
AI connected to your data and tools, then monitored and tuned in production.
Explore →Generative AI & LLM development
Products and features built on large language models.
Explore →LLM fine-tuning
Adapting models to your domain, terminology and output formats.
Explore →AI POC development
A focused proof of concept that tests an AI idea against real data.
Explore →Predictive analytics
Models that forecast outcomes from your historical data.
Explore →Computer vision
Systems that read and interpret images, scans and video.
Explore →How it works. An illustrative replay based on a delivered engagement, using sample data.
- 1Party namep.1
- 2Reference numberp.1
- 3Effective date§1
- 4Total amount§2Needs reviewVerified
New contract in the inbox. Extract the key fields and flag anything you are unsure of.
New document received
Running structured extractionStructured extraction complete
Classifying documentClassification complete
Checking extraction confidenceLow-confidence field flagged
Routing exceptions to manual reviewOnly the exception goes to review
- 1Update recordCRM · 1 record · 0.8s
- 2Send notificationEmail · 2 recipients · 1.1s
- 3Release paymentPayments · over approval limit · 2.4s
Resolve this request across our systems. Check with me before any payment.
New task received
Retrieving data across systemsData retrieved across systems
Reasoning and proposing actionsActions proposed
Executing low-risk actionsLow-risk actions executed
Checking action riskHigh-stakes action sent for approval
Waiting for human approvalApproved, action executed
Running evals and logging traceEvals passed, trace logged
AI solutions we have shipped. Each result comes from a delivered engagement.
AI document intelligence
Extraction and classification that sends only the exceptions to people.
>80% less manual review AI · Agent platformsAI agent platform
Agents retrieve, reason and act across systems, with human approval before high-stakes actions.
~40% less manual effort AI · HealthcareMulti-agent voice AI
Live voice agents for scheduling, verification and follow-up calls, escalating to a person when needed.
~50% fewer manual handling cases AI · LegalResearch & review assistant
Citation-grounded answers, each one traced back to its source document.
~50% faster review time AI · InsuranceFull-stack AI platform for insurance
Fragmented policy, claims and correspondence data connected into one structured workflow.
~2.5x faster processing AI · Workflow automationWorkflow automation platform
AI extraction feeding a deterministic rules engine, with consistency checks built in.
~70% faster document prepHave an AI idea you want to test against real data?
Industries we have delivered AI in. Each one links to the engagement behind it.
The technology behind our AI systems. The right stack depends on the model, the data, the architecture and where it runs.
Programming languages
- Python
- Java
- JavaScript
- TypeScript
- C++
- R
- Go
- SQL
- Swift
- Kotlin
AI and machine learning frameworks
- TensorFlow
- PyTorch
- Scikit-learn
- Keras
- XGBoost
- LightGBM
- JAX
- Hugging Face Transformers
Generative AI and large language models
- OpenAI
- Anthropic Claude
- Google Gemini
- Meta Llama
- Mistral AI
- Cohere
- Hugging Face
- OpenRouter
- LangChain
- LlamaIndex
AI agents and orchestration
- LangGraph
- AutoGen
- CrewAI
- Semantic Kernel
- Agentic workflows
- Tool calling
- Function calling
- Multi-agent systems
Natural language processing
- Text classification
- Sentiment analysis
- Named entity recognition
- Text summarization
- Semantic search
- Question answering
- Embeddings
Computer vision
- OpenCV
- YOLO
- Detectron2
- Image classification
- Object detection
- OCR
- Image segmentation
- Facial recognition
- Video analytics
Speech and voice AI
- Speech-to-text
- Text-to-speech
- Voice recognition
- Voice assistants
- Conversational voice AI
- Audio processing
Data engineering and processing
- Apache Spark
- Pandas
- NumPy
- Apache Kafka
- Apache Airflow
- Databricks
- dbt
Databases and data storage
- PostgreSQL
- MySQL
- MongoDB
- Redis
- Microsoft SQL Server
- Amazon DynamoDB
- Elasticsearch
- Snowflake
Vector databases and semantic search
- Pinecone
- Weaviate
- Milvus
- Qdrant
- Chroma
- pgvector
- Elasticsearch vector search
Cloud and AI infrastructure
- AWS
- Microsoft Azure
- Google Cloud
- Amazon SageMaker
- Azure Machine Learning
- Google Vertex AI
- Databricks
Containers and orchestration
- Docker
- Kubernetes
- Amazon EKS
- Azure Kubernetes Service
- Google Kubernetes Engine
- Terraform
MLOps and model operations
- MLflow
- Kubeflow
- DVC
- Model versioning
- Model monitoring
- CI/CD pipelines
- Automated retraining
- Performance tracking
AI integration and APIs
- REST APIs
- GraphQL
- Webhooks
- Microservices
- API gateways
- SDK integrations
- Third-party AI APIs
Backend development
- Node.js
- Django
- FastAPI
- Flask
- Spring Boot
- .NET
- Express.js
Frontend and application development
- React
- Next.js
- Angular
- Vue.js
- React Native
- Flutter
- Android
- iOS
AI evaluation and observability
- Model evaluation
- Prompt testing
- Hallucination detection
- Latency monitoring
- Cost tracking
- Output quality assessment
- AI observability
- Langfuse
Development and collaboration tools
- Git
- GitHub
- GitLab
- Bitbucket
- Jenkins
- Jira
- Postman
From idea to production. Four stages, with a working version reviewed at each one.
-
Discovery
Map the workflow, the systems and data involved, and what good looks like.
Discovery notesDone
- The workflow to improve
- Systems and data involved
- How success is measured
-
Scope & architecture
Agree the architecture, success measures and delivery milestones.
Solution designDone
- Architecture and model choice
- Integration points
- Delivery milestones
-
Build
Build against real data, with a working version reviewed at each milestone.
Working buildDone
- Built against real data
- Evals on representative cases
- Review at each milestone
-
Ship & support
Roll out to production with monitoring and a defined support window.
Production rolloutDone
- Production deployment
- Monitoring
- Defined support window
Why Avinya for AI. Built for real operations, measured against real results.
Results you can check
Every number on this page links to the engagement it came from.
People stay in control
Approval checkpoints, escalation paths and exception review are designed in from day one.
Traceable by default
Citations, audit trails and logs, so outputs can be verified rather than trusted blindly.
Production, not demos
Built to run against real systems and real data, with monitoring once live.
Full-stack delivery
Data pipelines, models, product and integrations from one team.
AI and Web3 under one team
One studio for AI systems and, where it helps, on-chain infrastructure.
Results from our AI work. Each number links to the engagement it came from.
Engagement models. Pick the shape that fits where you are.
Dedicated team
A dedicated team that works as an extension of yours, from first release to scale.
Project-based
A defined scope, milestones and delivery date for a specific product or workflow.
Consulting & advisory
Architecture and readiness advice before you commit to a build.
What our clients say.
“We needed a platform that could handle complex construction workflows without breaking down every week. Avinya Labs delivered exactly that. What stood out even more was their commitment after launch: when a critical issue came up, the team stayed up until midnight to make sure we weren't left hanging.”
“Avinya Labs built our full-stack AI solution … Their expertise accelerated our launch and significantly reduced execution risk.”
“Avinya Labs built our AI travel chatbot … A highly capable team that delivers ahead of the curve.”
AI development FAQs.
What kinds of AI systems do you build?
AI agents, document intelligence, voice AI, chatbots, workflow automation and complete AI SaaS products, usually connected into existing business systems.
Which AI models do you use?
We evaluate models against your real workflow and choose per task. The architecture is designed so models can change later without rebuilding the product.
How long does a project take?
It depends on scope and integrations. We agree milestones up front and review a working version at each one.
How do you handle our data?
Access is scoped to what the system needs, with role-based permissions and audit trails where records change. We agree data handling during discovery.
Can you work with our existing product and team?
Yes. We can add AI into an existing product, work alongside your engineers, or run the build end to end.
Ready to turn your vision into reality?
Tell us the problem, the data, and where manual effort sits today. We'll map the path from MVP to scale.
Or email contact@avinyalabs.co