AI & Machine Learning Development — LLM Apps, Automation & Predictive Models
Hurain Technologies has been engineering software since 2010 and delivers AI & machine learning development to businesses worldwide: remotely from India, available 24/7, on milestone-based scopes, with one project manager and full source-code ownership.
Scope typically covers LLM assistants & RAG, document automation and AI agents & workflows. A first production release usually takes 4–6 weeks (proof of value), and a full platform 3–5 months. Every build is scoped against data-protection rules on automated decision-making and the EU AI Act where applicable.
Quick answer
What does Hurain Technologies build for AI & machine learning?
Hurain Technologies builds production AI: LLM-powered assistants and document automation with retrieval (RAG), fraud and risk models, demand forecasting, computer vision and AI agents that act inside your systems — with evaluation, guardrails, cost control and data privacy designed in from the start.
Reviewed by Shahnavaz Syed, Founder · Last updated
Overview
What AI & machine learning with Hurain Technologies looks like
Most AI projects stall between a promising demo and a dependable product. The gap is evaluation, data quality, integration and cost — so that is where we focus. Every AI feature we ship has a test set, measurable accuracy targets and a fallback when the model is unsure.
We choose the simplest approach that works: a well-prompted LLM with retrieval over your documents, a classical ML model trained on your data, or a fine-tuned model when neither is enough. We are model-agnostic and design for swapping providers as prices and capabilities change.
Your data stays yours. We use enterprise API terms that exclude training on your data, redact sensitive fields, and can deploy open-weight models in your own cloud when data may not leave it.
Capabilities
AI & Machine Learning features we deliver
LLM assistants & RAG
Chat and search over your documents, policies and product data, with citations.
Document automation
Extract, classify and validate data from invoices, IDs, contracts and forms.
AI agents & workflows
Agents that call your APIs to complete tasks, with human approval where it matters.
Fraud & risk models
Real-time scoring for transactions, onboarding and claims.
Forecasting & recommendations
Demand, churn and next-best-offer models trained on your history.
Evaluation & MLOps
Test sets, monitoring, drift detection, cost dashboards and versioned deployments.
Use cases
Customer support automation
Answer and route tickets, draft replies and summarise conversations.
Back-office automation
Turn manual document processing into straight-through workflows.
Fraud prevention
Detect suspicious payments, accounts and claims before losses occur.
Sales & retail intelligence
Forecast demand, personalise offers and price dynamically.
Cost & timeline
How much does AI & machine learning cost and how long does it take?
Delivery time is agreed around your scope and split into milestones you sign off before paying. Price is driven by scope rather than a fixed rate card — these are the factors that move it most:
- Data readiness and labelling effort
- LLM API usage vs self-hosted models
- Accuracy targets and evaluation depth
- Number of systems the AI must act in
- Privacy and on-premise requirements
- Real-time vs batch inference
Technology
Models
- Claude
- GPT
- Llama / Mistral (open-weight)
- scikit-learn / XGBoost
Frameworks
- Python
- PyTorch
- LangGraph
- LlamaIndex
Our delivery process
- 1
Use-case & data assessment
Pick the highest-value use case and confirm the data exists to support it.
- 2
Proof of value
Working prototype measured against an agreed evaluation set.
- 3
Production build
Integration, guardrails, monitoring and user interface.
- 4
Rollout
Pilot group, feedback loop and cost tuning.
- 5
Continuous improvement
Retraining, prompt updates and model upgrades.
Standards we build to
- Data-protection rules on automated decision-making
- The EU AI Act where applicable
- Human review for high-impact decisions
Live Demos
A selection of platforms we've designed and built
Real, working builds across fintech, compliance, healthcare, and commerce — the same engineering team would build your ai & machine learning project.
Nexa
SaaS-style product dashboard and workflow UI for a fintech platform.
Open live demoAML Compliance Suite
Anti-money-laundering compliance and case-monitoring suite.
Open live demoDebt Management
Debt management and collections tracking platform.
Open live demoUMARSOB Data
Android VTU/data-reseller platform with wallet, agent/referral system, and admin panel.
Open live demoHospital Management
Hospital/clinic management system covering patient records, appointments, staff, and billing.
Open live demoDMI CHW App
Offline-first Community Health Worker counseling app with a central management platform, built for an NGO client.
Open live demoHomemakers Pro
Enterprise operations system for a domestic staffing agency covering bookings, staff, and client management.
Open live demoE-Commerce (Multi-Locale)
E-commerce storefront demo with multi-language, locale-based support.
Open live demoMars
Legal web application prototype.
Open live demoBusiness value
What AI & Machine Learning does for your business
Benefits for your company
- Automate repetitive work. Models and workflows that handle classification, support and document processing.
- Decisions from your own data. Forecasting and scoring trained on your records.
- Human-in-the-loop controls. Review steps and monitoring so automation stays accurate.
How it can earn or save money
- Lower service cost. Automation handles more volume without proportional headcount.
- Personalised selling. Recommendations and targeting raise conversion and order value.
- AI features as paid products. Offer intelligent features to customers on premium plans.
Illustrative revenue and saving lines, not guaranteed results: outcomes depend on your market, licences and execution.
How we work
How we deliver AI & Machine Learning
Every ai & machine learning engagement follows the same staged, quality-gated process — shaped around your requirements. You see progress every day, review it every week, and give written sign-off at every milestone before any payment is due.
- 01
Discover
Metrics agreed- Use-case workshops
- Data availability audit
- Success metrics agreed
- Signed scope
- 02
Design
Model design OK- Feature & model design
- Data pipeline design
- Human-review workflow
- Explainability plan
- 03
Build
Model accepted- Model training sprints
- Feature pipelines
- Evaluation reports
- Demo every sprint
- 04
Secure & Test
Accuracy verified- Accuracy & drift tests
- Bias checks
- Adversarial tests
- UAT with analysts
- 05
Deploy
Shadow run OK- Shadow-mode launch
- Gradual rollout
- Model monitoring
- Go-live checklist
- 06
Handover
Handover signed- Role-based sessions
- Recorded walkthroughs
- Admin & ops runbooks
- Documentation handover
- 07
Support
Drift monitored- Dedicated engineer
- SLA helpdesk
- Patches & upgrades
- Quarterly reviews
Client sign-off at every milestone — you approve the working result before you pay.
You always know what was done today — and what happens next
A written daily update, a weekly work overview and a live demo every sprint — so there are no surprises at milestone time.
Every working day
- What was completed today
- What is planned for tomorrow
- Blockers and decisions needed from you
- Links to builds you can try
Every Friday, with a live call in your business hours
- Features completed and demo recordings
- Progress against the current milestone
- Risks, open questions and change requests
- Plan and priorities for next week
End of every sprint and milestone
- Working software demonstrated live
- Your feedback captured in the backlog
- Quality-gate checklist shared
- Written sign-off before any payment
Payment plan
Pay only for work you have accepted
Milestones are customised to your requirements — six or more is typical, and delivery time is agreed around your scope. Every payment after the advance is released only after you have seen the working result and given written sign-off. Here is an example plan:
| Payment | Milestone & acceptance | Share |
|---|---|---|
| Advance | Contract signing Signed contract; use-case workshops and data audit. | 10% |
| Milestone 1 | Success metrics approved Data plan, metrics and review workflow signed off. | 15% |
| Milestone 2 | Baseline model Pipelines built; baseline model evaluated. | 15% |
| Milestone 3 | Production model Tuned model, review workflow and dashboards in staging. | 15% |
| Milestone 4 | Validation passed Accuracy, drift and bias tests passed. | 15% |
| Milestone 5 | Shadow-mode sign-off Analysts accept results in shadow mode. | 15% |
| Milestone 6 | Live & handed over Gradual rollout, model monitoring and handover. | 15% |
| Total | 100% | |
- Number of milestones and splits set around your scope
- Every milestone is a working, demonstrated result
- No payment is due until you sign off
Warranty & annual support
Protected after launch — warranty and annual support for your AI & Machine Learning project
Go-live is where your ai & machine learning product starts earning — so we stay accountable for it. Every project includes a free 90-day defect warranty. After that, the same team that built it keeps it secure, updated and running on a fixed annual fee agreed up front — no open-ended hourly billing, no surprise invoices.
Included free
90-day warranty
Any defect found in the first 90 days after go-live is fixed free of charge.
- Every delivered feature covered
- Fixes tested and deployed to production
- Same engineers who built it
Fixed-cost annual package
30% of project cost
per year for Annual Support & Maintenance, with a dedicated developer assigned to your ai & machine learning platform. A fixed price, known in advance.
| Service | Included in the annual package |
|---|---|
| Dedicated developer | One named developer assigned to your product for fixes, enhancements and optimisation. |
| Bug fixes & security patches | Critical issues resolved within 24 hours; standard issues within 5 business days. |
| Upgrades & new releases | Framework, library and platform updates plus new versions of what we built, at no additional cost. |
| Helpdesk | Email and phone support for your team and administrators; 4-hour response for critical issues. |
| Backup monitoring | Daily backup checks and a quarterly restore test. |
| Security review | Periodic audit-trail review and security configuration check. |
| Model monitoring | Accuracy and drift tracked; models retrained when performance drops. |
| Data pipeline checks | Feature pipelines and data quality checked so predictions stay reliable. |
Source code & IP ownership
100% of the source code and IP is owned by you
For every custom ai & machine learning project, upon full and final payment the complete source code and intellectual property are transferred to you — so you can host, maintain and enhance the system with any developer.
- Model code, training pipelines and notebooks
- Trained model files and evaluation reports
- Feature definitions and data-pipeline code
- Complete Git repository with full commit history
- Database schemas, migrations and seed data
- Configuration, CI/CD and deployment scripts
- API documentation and a deployment guide
No lock-in
No forced upgrades
No subscription trap
Your code lives in your own repository from the first commit.
Continuous enhancement
Launch is just the beginning — keep shipping with your own dedicated team
Your ai & machine learning platform should get better every month, not stand still after go-live. Start with one dedicated developer working on your priorities across apps, dashboards and backend — and grow to a full team of developers and support members whenever your roadmap demands it.
Dedicated team, your way
From one developer to a full team
Pricing is based on the team members you need — tell us your requirements and we will quote your team.
- Start any time after launch
- Hire developers as you need them
- Scale up, scale down or pause
What your team can take on after launch
- New models and use cases
- Better accuracy through new data and features
- Dashboards, review tools and automation
Need more hands? Add developers and support members as your requirements grow
Start with one person and add only the roles your ai & machine learning roadmap needs — each is quoted to your requirements.
Development team
ML engineer
Trains, deploys and improves models in production.
Data engineer
Builds the feature pipelines and data-quality checks models rely on.
Backend developer
Adds the APIs, business logic and data models behind new features.
Frontend developer
Builds and refines the web screens and dashboards your users see.
QA engineer
Writes and runs manual and automated tests before every release.
Support team
L1 helpdesk support executive
First contact for your users and staff — logs, triages and resolves common issues.
L2 technical support engineer
Investigates bugs, data issues and integrations, and escalates to developers with full context.
Model operations support
Watches model health and works through human-review queues.
Data-quality support analyst
Checks incoming data and fixes pipeline issues.
Our Approach
Our approach to development methodologies
Our approach to custom software engineering draws on a range of methodologies, each selected to match the needs of your AI & machine learning project.
Agile Scrum
Best for: Evolving products
Two-week sprints with a working demo at the end of each, so AI & machine learning priorities can change as you learn from users.
Kanban
Best for: Continuous delivery & support
A visual flow of small tasks with work-in-progress limits — ideal for maintenance, integrations and post-launch improvements.
Fixed-scope (Waterfall-style)
Best for: Well-specified builds
Requirements signed off up front with a fixed timeline and price — best when scope is clear and change is unlikely.
Lean MVP
Best for: New ventures
Build the smallest AI & machine learning release that proves demand, measure it with real users, then invest where the data points.
DevOps & CI/CD
Best for: Every project
Automated tests, infrastructure-as-code and push-button deployments so releases are frequent, reversible and boring.
Security-by-design (DevSecOps)
Best for: Regulated & high-value systems
Threat modelling, dependency scanning and code review built into each sprint rather than a pen test at the end.
Why we're different
What sets Hurain Technologies apart
Plenty of agencies can build AI & machine learning. Here is what sets us apart for clients worldwide.
Engineering depth, not a reseller
Your AI & machine learning project is designed and built by our own in-house engineers — no hidden subcontracting chain between you and the people writing code.
Built for your market, not a template
Payments, tax, language and data-protection requirements for your target market are part of the design from day one instead of retrofitted after launch.
Transparent, senior-led delivery
A named project lead, a shared backlog, fortnightly demos and direct Slack access to the engineers — you always know what is being built and why.
Cost advantage without cutting corners
Delivering from India gives clients worldwide senior engineering at a fraction of typical onshore agency rates, with the same code-review, testing and security standards.
You own everything
Source code lives in your repository from the first commit; IP, infrastructure accounts and documentation transfer to you in full.
We stay after launch
Monitoring, updates and a support SLA mean the team that built your product is the team that keeps it running.
Flexible engagement models
How we work with AI & machine learning clients worldwide
Ways to work together, depending on how your team and roadmap are set up.
Dedicated Development Team
An extended team of AI & machine learning engineers, QA and architects working exclusively on your product, managed day-to-day by you with our engineering leadership behind them.
Best for: Long-term products and evolving roadmaps
Fixed-Cost Delivery
A clearly scoped AI & machine learning build with a defined timeline and price — ideal for a well-specified MVP, integration or launch product.
Best for: MVPs and clearly defined projects
Hybrid Engagement
Keep product and regulatory decisions close to your team while our specialists handle deep engineering remotely, with workshops or on-site visits at key milestones.
Best for: Enterprises and regulated businesses
Why businesses choose us
Why businesses choose Hurain Technologies
16+ years of engineering depth
Custom software engineering with in-house teams across web, mobile, cloud, AI, payments and blockchain.
Security-first by default
Encryption, least-privilege access, audit logs — and MPC/HSM custody and audited smart contracts where money is on-chain — designed in, not retrofitted.
Regulatory-aware architecture
Designed with your target market's regulatory direction in mind and built alongside your licensed local legal counsel.
Direct access, no layers
Direct Slack or Teams access to your development team during the build, and the same people for post-launch support.
Business benefits
What you gain
Faster time to market
An experienced AI & machine learning team with proven components means your first release ships in weeks, not quarters.
Security-first architecture
Secure from day one, rather than patched after an audit or incident.
Aligned compliance groundwork
Controls, logs and data handling built around your target market's requirements so reviews go faster.
Lower total cost of ownership
Clean, documented, tested code that your own team can maintain — plus post-launch monitoring and support.
What happens next
From your AI & machine learning enquiry to a working demo — in about a day
- 01Within 10 minutes
We respond to your enquiry
Send your AI & machine learning enquiry by form, email or WhatsApp — a few lines is enough. Our team replies within 10 minutes, any day, any time, to set up a meeting at a time that suits you.
- 02Requirements meeting
We understand your requirements
In a focused meeting we go deep on your users, features, integrations, timeline and budget — so we build exactly what your business needs. NDAs signed on request.
- 03Within 24 hours
You see a demo of your AI & machine learning
Within 24 hours of our meeting we prepare and share a demo — so you see your AI & machine learning taking shape before you commit to anything.
- 04As per your budget
We share a tailored proposal
A clear proposal for your AI & machine learning project with scope, milestones, team and timeline — shaped around your budget, with no hidden costs and no obligation.
Available 24×7 — three 8-hour shifts, every day
FAQ
AI & Machine Learning: frequently asked questions
What is AI & machine learning?
How long does AI & machine learning take?
How much does AI & machine learning cost?
Will my data be used to train public AI models?
How do you stop the AI from making things up?
How long before we see results?
Do you build the complete AI & machine learning solution, or only integrate with what we already use?
We are not sure about our budget yet. Can you still help?
By location
AI & Machine Learning by country
Each country page covers local payment methods, tax, data-protection law, 24/7 support and delivery timelines.
Priority markets
Major cities
All countries
Related solutions
Related engineering services
Ready to start your AI & machine learning project?
Share your idea — we respond in 10 minutes, share a demo within 24 hours of our meeting, and a proposal as per your budget.