How Long Does It Take to Implement AIImplement
8-14 weeks for a working AI feature or MVP shipped by senior engineers. Fixed price quotes after a 2-week Roadmap phase.
How long does it take to implement AI depends on what you are building. For a custom chatbot using OpenAI or Anthropic APIs with your proprietary data, IRPR delivers a functional MVP in 10-12 weeks. This timeline covers prompt engineering, vector database setup (Pinecone or Weaviate), and a React or Next.js frontend.
A broader AI implementation like a predictive analytics engine for internal dashboards takes 12-14 weeks. That includes model selection, training data pipelines, API integration, and a deployment on AWS SageMaker or GCP Vertex AI. Pricing starts at $70,000 for a focused AI feature and ranges up to $250,000 for a full AI core product. Every project starts with a fixed-price quote in week 2.
Startup founders come to us for a 12-week AI MVP to show investors. Compliance officers at Fintech companies need a PCI-DSS-compliant fraud detection AI within 3 months. Healthcare product managers hire IRPR to implement a HIPAA-compliant AI clinical note summarizer in 10 weeks. Operations directors in Logistics want a custom RPA and AI workflow to reduce manual data entry.
Types of software we ship.
AI Chatbot with RAG
A support or sales chatbot using retrieval augmented generation. Integrates your docs via Pinecone and OpenAI. Ships in 10 weeks.
Predictive analytics engine
A custom model for forecasting sales, churn, or inventory on your data stack. Deployed on AWS SageMaker. 12-14 week timeframe.
AI document processing
Extracts data from PDFs or forms using Google Document AI or AWS Textract. Routes to your CMS or database in 8 weeks.
Recommendation system
Product or content recommendations using collaborative filtering and TensorFlow. Integrates with your catalog API. 12 weeks.
Internal AI copilot
AI tool for your team to query SQL databases with natural language. Uses LangChain and Snowflake. 8-10 week MVP.
Computer vision AI
Image or video analysis for defect detection or moderation. Built with PyTorch or Roboflow. Integrates your existing camera pipeline. 14 weeks.
AI voice agent
Automates appointment booking via phone using ElevenLabs and Twilio. Deploys as a fully connected voice pipeline in 8 weeks.
Custom LLM fine-tune
Fine-tune a Llama 3 or Mistral model on your proprietary data for a unique task. Deployed with vLLM on your private cloud in 14 weeks.
We build for every business type.
startups and new ventures
regulated enterprises
ecommerce and retail
service and operations teams
media and data companies
Why most AI implementation timelines slip
Generic dev shops turn a 10-week project into a 6-month mess. Here is what happens.
Shops that quote hourly rates will pivot your AI into a research project. They charge you to explore different models with no end date. Your 8-week chatbot becomes a 4-month money drain because they are learning on your dime, not executing from a proven playbook.
Data readiness is the blocker they hide from you. They do not tell you that cleaning schemas takes 3 weeks or that a vector database like Pinecone needs a specific structure. IRPR flags this in the Roadmap week so you never get a surprise delay at week 8.
How a fixed price locks your AI timeline
A 2-week Roadmap phase removes the guesswork. You know the cost and the ship date before a single model is trained.
The traditional AI agency model bills by the hour. They have no incentive to finish. IRPR inverts this. Our Roadmap phase defines the exact scope, API integrations (OpenAI, Anthropic, Gemini), and database choices (PostgreSQL, Pinecone). By day 14, you have a fixed price and a 10-week timeline.
You get a clickable design prototype and a full technical architecture document. That document includes the ML model spec, the data pipeline diagram, and the UI component tree. You own the deliverables at the end of week 2 regardless of build. No sunk cost trap.
- Hourly billing incentivizes delays
- No POC in the first month
- Hidden data cleaning fees pile up
- Overpromises a one-week feature that takes six
- No HIPAA or PCI compliance track record
- Junior devs practicing ML on your code
- Fixed price locked by week 2
- Functional prototype in 8-12 weeks
- Data readiness review in the Roadmap
- Timeline includes QA and deployment
- HIPAA and SOC 2 compliant AI pipelines
- Senior engineers with 5+ years in MLOps
The 4 phases of AI implementation at IRPR
Every AI project moves through a consistent pipeline. You see progress weekly.
The Idea phase (week 1-2) nails the constraint. We define what data is available right now. We pick the model size with the cost per API call estimated. You leave this phase with a fixed price and a guaranteed 10-week delivery for a RAG chatbot, or up to 14 weeks for a custom fine-tuned model.
The Roadmap phase delivers a Figma prototype and a system architecture diagram. The Product phase (weeks 3-8) gets the AI endpoint working on dev servers with your data. The Release phase (weeks 9-12) handles load testing, security audit, and launch on your AWS or GCP account.
What you own after an AI implementation
The AI model, the code, the data pipelines. All in your cloud account. No vendor lock-in.
IRPR ships your complete AI stack as a deliverable. The source code, the model weights if fine-tuned, the vector database schema, and the CI/CD pipelines are all yours. We deploy to your AWS, GCP, or Azure. You get full admin access. We never hold your AI hostage on our servers.
- Full source code in your GitHub or GitLab repo
- Deployed AI endpoints on your cloud
- CI/CD pipeline with GitHub Actions
- Sentry or Datadog error tracking configured
- API documentation via Postman collection
- Load test report for 1000 concurrent users
- Vector database schema and backup scripts
- 30-day warranty on all delivered code
- HIPAA or PCI checkpoint sign-off if required
- Handover call with your ops team
What we ship in this practice.
10-week HIPAA clinical note summarizer
A hospital network needed an AI to summarize patient-doctor conversations into SOAP notes. IRPR used OpenAI Whisper for transcription and GPT-4 for note generation in a private AWS VPC. Reduced note-writing time by 9 hours per clinician per week. Tech: React, FastAPI, AWS HealthLake.
12-week ecommerce product recommendation engine
A fashion retailer wanted a Pinterest-like feed of recommendations. IRPR built a collaborative filtering model on their 200k SKU catalog using TensorFlow and integrated it into a Next.js frontend. 18% lift in average order value in the first month. Tech: Next.js, Flask, BigQuery, Vertex AI.
8-week logistics RPA and AI email parser
A freight broker processed 3000 emails daily manually. IRPR deployed an AI email classifier with Google Document AI and an RPA bot in 8 weeks. Handled 87% of inbound rate requests automatically. Tech: Python, Google Doc AI, UiPath, PostgreSQL.
14-week fintech fraud detection AI
A neobank needed real-time transaction scoring under 20ms latency. IRPR implemented a XGBoost model trained on their 5-year ledger and deployed via a Node.js microservice. Blocked 34% more fraud attempts than the previous rules engine. Tech: Node.js, XGBoost, Redis, AWS KMS encrypted store.
10-week real estate AI valuation model
A proptech startup needed an automated valuation model for off-market properties. IRPR trained a gradient boosting model on MLS comps and county assessor data. Ingested data from 12 counties via custom Python scrapers. Reduced manual comp time by 12 hours per analyst. Tech: Python, CatBoost, Airflow, Mapbox API.
8-week AI support chatbot for a SaaS company
A SaaS platform with 5000 users needed to deflect Tier-1 tickets. IRPR built a RAG chatbot on their Zendesk articles and API docs using Pinecone and GPT-4o. Deflected 42% of incoming chats in the first month. Tech: Next.js, Pinecone, OpenAI, Zendesk API.
Why teams hire us.
Fixed price locked in week 2
No open-ended AI research invoices. After a 2-week Roadmap phase, you get a fixed price. That number does not change. The average AI project starts at $70,000.
Ship in 8-14 weeks, not 6 months
Our process strips scope to core AI value. A RAG chatbot ships in 8-10 weeks. A custom fine-tuned model on private data ships in 14 weeks. We deploy a working AI endpoint by the final week.
You own the AI, not us
All code, data pipelines, and model weights go into your cloud account. No IRPR backend. No API key dependency. You get full intellectual property transfer at launch.
Senior MLOps engineers only
No junior devs learning TensorFlow on your budget. The team that built 200+ AI products works on yours. Every engineer has 5+ years in deploying models to production at scale.
Compliance by default
HIPAA, SOC 2, and PCI-DSS compliant AI architectures without the consulting upcharge. We document the data boundary, encryption at rest, and audit trail as part of the build. Not as an afterthought.
30-day warranty on all AI code
If the AI endpoint breaks due to a code defect, we fix it free for 30 days. Post-launch monitoring with Sentry and model drift alerts are included in the delivery.
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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