How do successful companies implement AI?implement AI
IRPR builds production AI in 8-12 weeks. Fixed pricing from $80K - $250K.
IRPR builds AI that ships. Successful companies don't experiment for years - they deploy a working AI feature in 12 weeks. We use OpenAI, LangChain, Pinecone, and custom models on AWS SageMaker to build chatbots, recommendation engines, and automated document processing. Every project starts with a clear roadmap, not a blank check.
What ships: a production-ready AI system, integrated with your existing stack. Typical timeline: 8-12 weeks from kickoff to release. Pricing: fixed quotes from $80K to $250K, based on scope. All projects meet SOC 2 and HIPAA requirements where needed. You own the code and the model.
Who hires IRPR: CTOs at mid-market SaaS companies who need a customer-facing AI chatbot; product managers at ecommerce brands wanting AI-powered product recommendations; founders validating an AI startup MVP; and enterprise innovation teams deploying internal AI tools for document search.
Types of software we ship.
AI Chatbot
A conversational interface for customer support or sales. Built with OpenAI Assistants API or Rasa, integrated with your CRM like Salesforce or HubSpot. Handles 10,000+ conversations/month.
Predictive Analytics Platform
A dashboard that forecasts churn, demand, or risk. Uses Python, scikit-learn, and Streamlit. Trained on your historical data, updated daily.
AI Document Processing
Extracts data from PDFs, invoices, and contracts. Uses AWS Textract, custom OCR, and LangChain for classification. Reduces manual data entry by 20 hours/week.
Recommendation Engine
Product or content recommendations based on user behavior. Built with collaborative filtering, PyTorch, and Redis. Deployed as an API inside your Next.js app.
AI Voice Assistant
A phone or in-app voice agent for booking, support, or FAQs. Uses ElevenLabs, Vapi, or Twilio. Integrates with your backend via REST APIs.
Fraud Detection System
Real-time transaction scoring to catch fraud. Uses XGBoost, feature pipelines on Kafka, and a dashboard in React. Flags 95% of suspicious transactions before settlement.
AI Content Generation
Generate product descriptions, marketing copy, or SEO pages at scale. Uses GPT-4 with fine-tuning on your brand voice. API endpoint returns ready-to-publish content.
Semantic Search Engine
Search that understands intent, not just keywords. Uses Pinecone or Weaviate vector database, embeddings from OpenAI, and a React frontend. Finds relevant documents across 1M+ records.
We build for every business type.
Healthcare
Fintech
Ecommerce
SaaS
Real Estate
AI implementation by the numbers
IRPR has shipped AI features for 200+ products across 50+ countries.
Companies that implement AI successfully don't wait for perfection. They ship a working model in 12 weeks, then iterate based on real user data. Our team of 15 senior engineers has built AI for fraud detection, chatbots, document processing, and recommendation engines. Every project starts with a fixed-price roadmap so you know exactly what ships and when.
The average AI project at IRPR costs $150K and runs 12 weeks. We use OpenAI, AWS, and Python because they're battle-tested. You get a production API, not a Jupyter notebook. 98% of our projects ship on time, and we've never missed a deadline due to technical debt.
How IRPR builds AI vs generic dev shops
Not all AI developers are the same.
A generic dev shop will assign a junior team, use hourly billing, and deliver a prototype that can't scale. IRPR assigns senior engineers who've built AI systems handling millions of requests. We write production code from day one, not throwaway demos.
With IRPR, you get a fixed price, a 12-week timeline, and a model you own. We integrate with your existing auth, database, and monitoring. No black boxes. No vendor lock-in. You get the code, the weights, and the documentation.
- No AI specialization
- Hourly billing with no cap
- 6+ month timelines
- Unclear deliverables
- No compliance expertise
- No model ownership
- AI-first engineering team
- Fixed price, no surprises
- 8-12 week delivery
- Roadmap with clear milestones
- SOC 2 and HIPAA compliant
- You own the model and code
How IRPR implements AI for your company
Four phases from idea to production.
Phase 1: Discovery. We audit your data, existing systems, and user needs. Output: a technical spec and a fixed-price quote. Phase 2: Roadmap. We design the architecture, pick the model, and define the API contract. You sign off before a single line of code. Phase 3: Build. Our engineers write the code, train the model, and set up CI/CD. Weekly demos keep you in the loop. Phase 4: Release. We deploy to your cloud, run load tests, and hand over documentation. You launch in 12 weeks.
Post-launch, we offer 30 days of free support. After that, we can train your team or provide ongoing maintenance. The code is yours to keep and modify.
What ships with your AI implementation
Every project includes these deliverables by default.
IRPR doesn't just hand over a model. You get a production-ready system with monitoring, error handling, and a CI/CD pipeline. We set up logging, alerts, and a dashboard so you can track performance. If you need compliance, we handle HIPAA or SOC 2 documentation.
- Source code in your Git repo
- CI/CD pipeline on GitHub Actions
- Model weights and training scripts
- REST API with OpenAPI docs
- Prompt engineering documentation
- Error tracking with Sentry
- Load testing report (10k requests/sec)
- Admin dashboard for monitoring
- User authentication integration
- Data pipeline for model retraining
What we ship in this practice.
AI Chatbot for Customer Support
A SaaS company reduced support tickets by 35% with a chatbot built on OpenAI. Handles 5,000 conversations/month. Tech stack: Next.js, Laravel, OpenAI API, Redis.
AI Document Processing for Insurance
An insurance firm automated claims processing, cutting manual review from 2 hours to 3 minutes per claim. Uses AWS Textract and custom ML models. Tech stack: Python, FastAPI, PostgreSQL, AWS Lambda.
AI Recommendation Engine for Ecommerce
A DTC brand increased average order value by 18% with product recommendations. Built with collaborative filtering and deployed as an API. Tech stack: Python, PyTorch, Redis, React.
AI Fraud Detection for Payments
A fintech startup reduced chargebacks by 60% with real-time fraud scoring. Processes 100,000 transactions/day. Tech stack: Python, XGBoost, Kafka, Streamlit.
AI Content Generation for Marketing
A media company generates 500 SEO articles per day with AI. Reduced content costs by 70%. Tech stack: GPT-4 fine-tuned, Node.js, MongoDB, Vercel.
AI Document Search for Property Management
A property manager reduced time to find lease agreements by 90% with semantic search. Queries across 500,000 documents. Tech stack: Weaviate, OpenAI, Node.js, AWS.
Why teams hire us.
Fixed price, not hourly
Every AI project gets a fixed quote after the Roadmap phase (week 2). No hourly billing, no surprise invoices, no scope creep charges. You know the cost before we write a line of code.
Ships in 12 weeks, not 6 months
We build production AI in 8-12 weeks. Our team of 15 senior engineers uses battle-tested frameworks and pre-built components to avoid the 6-month research trap. You launch before the market moves.
Senior engineers only
IRPR never staffs your project with junior developers. Every engineer has 5+ years of experience building AI systems. They've shipped models for fraud detection, NLP, and computer vision at scale.
You own the code and the model
We transfer all source code, model weights, and training data to your Git repo. No licensing fees, no vendor lock-in. You can modify, scale, or audit everything yourself.
Compliance without the headache
We build AI that meets SOC 2, HIPAA, and PCI-DSS where required. Documentation, audit logs, and access controls are included. Your legal team will approve.
Built for scale, not a demo
Every AI system we ship is tested for 10,000+ concurrent requests. We use AWS, GCP, or Azure with auto-scaling and monitoring. It won't crash when your users arrive.
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.