Industries / Construction
AI for construction, from drawing to quotation.
A connected workflow that takes a fit-out project from drawing to quotation, built for English and Chinese-speaking teams and sold as a SaaS product.
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What we built for construction. An AI SaaS platform for fit-out and construction.
Drawing to quotation
A 5-stage connected workflow, from drawing takeoff through to the final quotation.
English and Chinese
Multi-language support so mixed teams work in one system.
SaaS with payments
Built as a subscription product, with Stripe handling payments.
Model orchestration
OpenRouter routes requests across AI models.
Quality and cost monitoring
Langfuse traces every model call, so quality and cost can be tracked.
Support after launch
The team stayed on after launch, including fixing a critical issue late at night.
What else we can build for construction. Capabilities we offer. We have not delivered these in this industry yet.
Procurement support
Material lists matched to suppliers, with prices compared for approval.
Document control
Drawings, specifications and submittals organised and searchable.
Site reporting
Photos and notes turned into structured daily reports.
Change order tracking
Changes captured, priced and approved in one place.
Safety reporting
Incident notes and photos structured into reports for the safety officer.
Subcontractor documents
Insurance and licence documents checked, with expiry dates tracked.
Progress tracking
Site photos matched to the schedule, with delays flagged for the project manager.
Our construction work, and related systems. Each result comes from a delivered engagement.
AI SaaS for fit-out & construction
An AI SaaS platform from drawing to quotation, for English and Chinese-speaking teams.
5-stage connected workflow AI · Workflow automationWorkflow automation platform
AI extraction feeding a deterministic rules engine, with consistency checks built in.
~70% faster document prep AI · Document intelligenceAI document intelligence
Extraction and classification that sends only the exceptions to people.
>80% less manual reviewDoes your quoting still move through disconnected stages?
The technology behind our AI systems. Chosen per task, not per trend.
01 / 08
Models
The language models behind each feature, picked per task on cost, speed and quality.
- OpenAI
- Anthropic Claude
- Google Gemini
- Meta Llama
- Mistral AI
- OpenRouter
- Hugging Face
02 / 08
Agents and orchestration
How agents plan, call tools and hand work to each other.
- LangChain
- LlamaIndex
- CrewAI
03 / 08
Machine learning
Custom models for prediction, vision and classification.
- PyTorch
- TensorFlow
- scikit-learn
- OpenCV
04 / 08
Vector search and databases
Where your data lives, and how answers stay grounded in it.
- Pinecone
- Qdrant
- PostgreSQL
- Redis
- MongoDB
05 / 08
Data pipelines
Moving and preparing data so models see the right, fresh inputs.
- Databricks
- Snowflake
- Apache Spark
- Apache Kafka
06 / 08
Cloud and infrastructure
Where it runs, in your cloud or ours.
- AWS
- Microsoft Azure
- Google Cloud
- Docker
- Kubernetes
07 / 08
Evals and operations
Tracing, testing and monitoring once it is live.
- Langfuse
- MLflow
- GitHub
08 / 08
Product and apps
The product your users actually touch.
- Python
- FastAPI
- React
- Next.js
From first use case to production. Four stages, with a working version reviewed at each one.
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Discovery
Map the quoting process, the systems and data involved, and what good looks like.
Discovery notes
- Your stages from drawing to quote
- Languages and teams
- Commercial model
-
Scope & architecture
Agree the architecture, success measures and delivery milestones.
Solution design
- Platform architecture
- Model and payment choices
- Release milestones
-
Build
Build against real data, with a working version reviewed at each milestone.
Working build
- Working platform on real projects
- Team review
- Quality checks
-
Ship & support
Roll out to production with monitoring and a defined support window.
Production rollout
- Production launch
- Monitoring
- Support window
Why Avinya for construction. We built and support a construction SaaS product.
Delivered, not theoretical
A live SaaS platform for fit-out and construction.
Product, not just a tool
Payments, languages and monitoring built in, ready to sell.
Models that can change
Orchestration means AI models can be swapped without a rebuild.
We stay after launch
In the client's words, the team stayed up until midnight to fix a critical issue.
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.
AI SaaS for construction
“Avinya Labs delivered exactly what we needed. When a critical issue came up, the team stayed up until midnight so we weren't left hanging.”
Guides on this topic. Plain answers to the questions buyers ask first.
How Intelligent Document Processing Works (2026 Guide)
Classify, extract, validate and route exceptions to people, and where it pays off.
Read the guide → GuideHow to Build an MVP: Steps, Timeline and Cost Drivers
Seven steps from one customer and one job to a first release.
Read the guide → GuideOperational AI Systems: A 2026 Guide for Enterprises
How AI moves from pilots into the daily operations of a business.
Read the guide →AI for construction FAQs.
What does the platform do?
It takes a fit-out or construction project from drawing to quotation through 5 connected stages, in English and Chinese.
Can we sell it as our own product?
The platform we built is a SaaS product with Stripe payments. Ownership and licensing are agreed in the contract.
How do you control AI costs?
Every model call is traced with Langfuse, so quality and cost can be monitored, and OpenRouter lets models change without a rebuild.
Where should we start?
With one task where the data exists and the risk is contained. We map it, agree what good looks like, and build a working version you can review before anything scales.
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.
How long does a construction AI platform take?
A prototype on a sample project takes about 6 to 9 weeks and a first version about 8 to 12 weeks. A production launch typically takes 3 to 5 months, depending on the stages and languages involved.
Can we sign an NDA first?
Drawings and pricing are commercially sensitive. Yes. We can sign an NDA before you share anything, and we agree ownership of the work in the contract before the work starts.
Where does AI for construction help most?
Paperwork: safety reports, subcontractor documents and progress tracking that people compile by hand. AI for construction flags gaps for a person to check, using the NIST AI Risk Management Framework for risk.
Free tool
How ready is your business for AI?
Twenty questions, about four minutes. You get a score across five areas and what to fix first.