Score every AI use case against ROI, feasibility, and data readiness. Launch a working MVP in 12 weeks with IRPR's fixed-price Roadmap.
IRPR builds AI project prioritization frameworks that score use cases using weighted criteria: ROI potential, technical feasibility, data maturity, and strategic alignment. We use Python-based scoring engines, SQL for data readiness checks, and React dashboards to visualize your AI portfolio.
In the Roadmap phase (weeks 1-2), we deliver a scored inventory of AI opportunities, a 12-week MVP build plan, and a fixed price for implementation. Projects range from $80K-$250K, with compliance baked in for HIPAA, PCI-DSS, or SOC 2 where needed.
CTOs at healthcare orgs hire us to rank AI diagnostic tools. Fintech heads of product use our scoring to pick fraud detection models. Ecommerce VPs prioritize recommendation engines. SaaS founders evaluate churn prediction features. Each gets a clear, defensible priority list.
Custom tool that weights and ranks AI ideas by ROI, effort, and data quality. Integrates with Jira and Airtable.
Real-time visualization of all AI projects with status, cost, and predicted ROI. Built with React and D3.js.
Surveys and data audits that measure data maturity, infrastructure gaps, and skill readiness. Exports to PDF.
Financial model that projects net savings or revenue uplift for each AI initiative. Connects to QuickBooks.
Gantt-chart timeline generator that sequences AI projects by dependency and resource availability. Syncs with Asana.
Lightweight kanban board for managing AI experiments, with built-in A/B testing and model registry integration.
Optimizes team assignments and compute budget across AI projects using linear programming. Exports to Excel.
Flags regulatory risks (HIPAA, GDPR) for each AI use case and suggests mitigation steps. Generates audit reports.
We've shipped over 200 AI-powered products across 50+ countries.
Our fixed-price Roadmap phase (2 weeks) delivers a scored AI project portfolio. Then we build the top-priority MVP in 12 weeks, on time 98% of the time.
Every engagement starts at $80K and scales based on scope. No hourly billing, no hidden fees.
Our 4-phase approach turns scattered ideas into a ranked, build-ready backlog.
Phase 1: Discovery. We interview stakeholders and catalog every AI idea, from chatbot to predictive maintenance. Phase 2: Scoring. We build a weighted matrix using Python and Airtable, scoring each use case on 10+ factors.
Phase 3: Roadmap. You get a 12-week implementation plan with fixed pricing. Phase 4: Build. We ship the top MVP, then iterate.
Every project includes these deliverables at no extra cost.
We don't just talk strategy; we ship working software. The Roadmap phase ends with a concrete, actionable plan.
Most dev shops build what you ask. IRPR tells you what to build first.
Generic agencies take your list and start coding. We apply a scoring framework to save you months of wasted effort.
With IRPR, you get a defensible priority list backed by data, not hunches.
Reduced AI project selection time from 6 months to 2 weeks. Scored 45 use cases on patient outcome impact and HIPAA compliance. Tech: Python, PostgreSQL, React.
Ranked 12 fraud models by expected loss reduction and integration effort. Deployed MVP in 10 weeks. Tech: FastAPI, Redshift, Grafana.
Projected $2.3M annual revenue uplift from personalized recommendations. Built a what-if simulator. Tech: Streamlit, BigQuery, Shopify API.
Prioritized 8 IoT use cases using sensor data readiness scores. Saved $400K/year in downtime. Tech: Node.js, InfluxDB, AWS IoT.
Evaluated 6 churn models against data maturity and integration cost. Launched top model in 8 weeks, reducing churn by 15%. Tech: Python, Snowflake, dbt.
Scored 20 AI initiatives on fuel savings and driver adoption. Built a proof-of-concept in 12 weeks. Tech: Go, PostGIS, Mapbox.
The Roadmap phase ends with a fixed quote for your top-priority AI project. No hourly billing, no scope creep. 200+ clients have used this model.
We don't just build; we score. Every engagement includes a weighted matrix with 10+ criteria, delivered in Airtable. You see exactly why we ranked each project.
No junior devs. Your project is built by engineers with 8+ years in ML, data engineering, and cloud. We've deployed models at scale for 50+ countries.
We compress the typical AI build cycle from 6-12 months to 12 weeks. You test real user feedback before committing to a full product. 98% on-time rate.
You own all code, data, and models from day one. We deploy to your AWS, GCP, or Azure account. No proprietary black boxes.
HIPAA, PCI-DSS, SOC 2, GDPR: we bake compliance into the scoring. AI projects that touch sensitive data get flagged early and designed accordingly.
Every engagement runs through the same four-stage pipeline. Predictable by design.
30-minute discovery call. No deck. We'll tell you honestly what it takes, how long, and how much.