Should I build custom AI or buy existing software?custom AI
IRPR builds custom AI in 12 weeks for $80K-$250K fixed price. You own the code, the data, and the model weights.
IRPR builds custom AI software for companies that have outgrown off-the-shelf AI tools. We develop agentic workflows, NLP pipelines, computer vision models, and predictive analytics using Python, TensorFlow, PyTorch, and LLMs like GPT-4 or Claude.
A custom AI system ships in 12-14 weeks at a fixed price of $80K-$250K. We integrate with your existing APIs, databases, and cloud infrastructure, and deliver HIPAA or SOC 2 compliant systems as needed.
Healthcare CTOs needing HIPAA-compliant AI diagnostics, fintech founders building fraud detection, ecommerce operators wanting personalized recommendation engines, and SaaS companies integrating AI assistants into their products hire IRPR for this decision.
Types of software we ship.
Custom AI chatbot for customer support
Uses GPT-4 and RAG pipelines to answer domain-specific questions, integrated with Zendesk and Salesforce.
Predictive maintenance AI for manufacturing
Analyzes IoT sensor data with TensorFlow to predict machine failures, cutting downtime by 40%.
AI-powered document processing
Extracts and classifies data from PDFs, invoices, and contracts using OCR and NER, connects to DocuSign.
Personalization engine for ecommerce
Recommends products in real time via collaborative filtering and Redis caching, lifts conversion by 25%.
AI-driven recruitment screening tool
Scores resumes against job descriptions with NLP, integrates with Greenhouse and Workday.
Custom medical image analysis AI
Detects anomalies in X-rays and MRIs using convolutional neural nets, 95% accuracy, HIPAA compliant.
AI-based fraud detection system
Monitors transactions with XGBoost on AWS Lambda, flags suspicious activity in under 50ms.
AI agent for automated workflow orchestration
Triggers actions across CRM, email, and databases using LangChain and Zapier, saves 10+ hours/week.
We build for every business type.
Healthcare
Fintech
Ecommerce & Retail
SaaS & Technology
Manufacturing & Logistics
Custom AI by the numbers
Data from 200+ AI projects shows why building custom beats buying.
Off-the-shelf AI tools promise quick wins but lock you into rigid workflows. Custom AI adapts to your data, grows with your team, and protects your competitive edge.
IRPR ships custom AI modules in 12 weeks, from data pipelines to deployed APIs, with warranties and full IP ownership.
Build vs. buy: the real difference
When you buy AI software, you inherit someone else's roadmap.
Vendor AI tools like ChatGPT Enterprise or Salesforce Einstein offer general capabilities. Customization costs extra, and you never fully own the model. Your data trains their general model, not your proprietary advantage.
IRPR builds AI that fits your exact workflow. You own the code, the model weights, and the data. No per-user fees, no feature request queues, no vendor lock-in.
- Generic models that serve all industries
- Per-user licensing costs scale up
- Limited customization, no new features unless vendor adds them
- Your data trains their global model
- Vendor lock-in, hard to migrate
- Support tickets go to a queue
- Models trained on your specific data
- Fixed price, no per-user fees after launch
- Unlimited customization - it's your software
- Your data stays private, yours alone
- Full code ownership, no vendor dependency
- Dedicated engineering team on Slack
How IRPR builds vs. buys AI systems
4 phases from idea to production AI.
Our process for custom AI starts with a fixed-price Roadmap that compares build vs. buy costs, so you decide with data.
We deliver the system in 12 weeks, with weekly demos and a 2-week QA sprint before launch. After that, you can extend the team for ongoing training and monitoring.
What ships with a custom AI build from IRPR
More than just code, a complete AI system.
When you build with IRPR, you get a production-grade system, not a prototype. We include everything you need to operate, secure, and scale.
- Source code in your Git repository (GitHub, GitLab, Bitbucket)
- CI/CD pipeline with GitHub Actions or GitLab CI
- Docker containers and Kubernetes configs
- API documentation (OpenAPI/Swagger)
- Model training scripts and datasets
- Monitoring dashboards (Grafana, Sentry)
- HIPAA/SOC 2 audit logs if required
- 24/7 support for 90 days post-launch
What we ship in this practice.
Fraud detection system for a neobank
Reduced fraudulent transaction losses by 70% within 3 months. Built with Python, XGBoost, AWS Lambda, integrated with Plaid for banking data.
HIPAA-compliant patient triage chatbot
Cuts nurse call volume by 50% in a 200-bed hospital. React frontend, Node.js, AWS HealthLake, HIPAA compliant on private VPC.
Real-time inventory forecasting for retail chain
Lowers stockouts by 40% across 150 stores. Uses TensorFlow, BigQuery, and Google Cloud Run, processes 500K SKUs daily.
Resume screening AI for HR tech startup
Processes 10,000 applications/day with 92% accuracy. Python, spaCy, PostgreSQL, integrated with Greenhouse API.
AI-based medical image analysis for radiology lab
Detects lung nodules with 95% accuracy, scans 300 X-rays/hour. PyTorch, DICOM, HIPAA compliant on Azure.
Customer sentiment analysis for SaaS helpdesk
Triggers escalation within 2 minutes on negative sentiment, reduces churn by 15%. Next.js, FastAPI, HuggingFace, Intercom integration.
Why teams hire us.
Fixed price, not hourly billing
We quote your custom AI build after a 2-week Roadmap phase. Fixed price, no surprise invoices, no scope creep.
12-week delivery window
From signed contract to production, the average build takes 12 weeks. We compress timelines with a dedicated senior team.
Full IP and code ownership
You own everything we build: code, model weights, training data. No licensing fees, no restrictions.
HIPAA, SOC 2, GDPR compliant
We build and certify for your required compliance from day one. Audit logs and security protocols baked in.
Dedicated senior engineers
No junior devs. Your team has 3-5 engineers with 8+ years of AI/ML experience.
Post-launch support included
90 days of incident response and minor updates, then an optional retainer for ongoing model retraining.
Idea → Roadmap → Product → Release.
Every engagement runs through the same four-stage pipeline. Predictable by design.
Questions clients ask first.
Related services and industries.
Ready to build? Let's talk.
30-minute discovery call. No deck. We'll tell you honestly what it takes, how long, and how much.
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