Can AI work with my existing software?AI
IRPR integrates large language models, computer vision, and predictive analytics into your current stack without rebuilding. We connect to your APIs, databases, and apps and ship a working integration in 8-12 weeks.
IRPR connects AI models like GPT-4, Claude, or open-source alternatives from Hugging Face to your existing systems. We build integration layers that talk to your REST or GraphQL APIs, SQL databases (PostgreSQL, MySQL), NoSQL stores (MongoDB, DynamoDB), and third-party tools like Salesforce, SAP, or Shopify. No need to replace what already works.
We ship an integration module with Python/FastAPI or Node.js backends, Docker containers, and cloud infrastructure on AWS or GCP in 8-12 weeks. Project costs range from $60K to $200K depending on complexity. All data handling follows SOC 2 standards, with HIPAA and PCI-DSS options available.
CTOs bring us to add AI features to legacy .NET or Java systems. SaaS product managers hire us to embed chatbots or recommendations into their platforms. Operations directors task us with automating document processing from custom ERPs. Healthcare IT leaders integrate AI with EHRs under strict HIPAA rules.
Types of software we ship.
AI integration with CRM
Connect models to Salesforce or HubSpot for lead scoring, auto-replies, and sentiment analysis using their bulk APIs and streaming endpoints.
AI integration with ERP
Feed data from SAP or Oracle into demand forecasting models. We build async pipelines that push predictions back to the ERP via BAPIs or REST.
AI integration with EHR systems
Add clinical decision support to Epic or Cerner using HL7 FHIR APIs. HIPAA-compliant environments with de-identified data flows.
AI integration with ecommerce platforms
Real-time product recommendations on Shopify or Magento using Redis-backed feature stores and TensorFlow Serving via webhooks.
AI integration with HRIS
Automate resume screening and candidate matching in Workday or BambooHR using NLP models exposed via internal APIs with role-based access.
AI integration with marketing automation
Generate campaign content and A/B test subjects in Marketo or HubSpot using GPT-4 and a custom approval gateway.
AI integration with data warehouses
Enable natural language querying on Snowflake or BigQuery with a semantic layer that translates to SQL using LangChain and your metadata.
AI integration with custom legacy apps
Wrap old mainframe or .NET monoliths with a thin API layer (Kong, Apigee) to feed data into AI models without touching core logic.
We build for every business type.
Enterprise IT
Healthcare
Financial services
SaaS companies
Professional services
AI integration that plugs into your stack
Our integrations connect AI to your tools without replacing them.
Most AI projects fail because they start with a blank slate. IRPR starts with what you have. We map your existing APIs, database schemas, and business logic. Then we design an integration layer that streams data to and from AI models - no rip-and-replace. We've connected models to Salesforce APIs, PostgreSQL triggers, and Kafka streams across 200+ products.
The integration layer handles rate limits, retries, and data transformations. You keep your current UI, authentication, and workflows. The AI becomes another service in your architecture, called via REST or gRPC. Our engineers have deployed AI integrations for companies in 50+ countries, always prioritizing backward compatibility.
Why rebuild when you can integrate?
Generic dev shops push full rewrites. IRPR connects AI to what you already have.
A new platform from scratch takes 6-12 months and costs $300K-$800K. That delays AI value by quarters. An integration layer ships in 8-12 weeks and costs $60K-$200K. You get AI features running against your production data while the rest of the team continues as usual.
We build modular adapters that isolate AI logic from your core system. This means you can upgrade the model, swap vendors, or scale inference without touching your legacy stack. When a fintech client needed fraud detection on a 15-year-old mainframe, we put a thin API gateway in front, fed transactions to a XGBoost model, and returned scores in under 200ms.
- Insists on rebuilding the whole system
- No API-first design or versioning
- Months of discovery before a single line of code
- Hourly billing with open-ended costs
- Limited compliance experience with no audit trail
- No DevOps for AI pipelines
- Connects AI to your existing APIs and databases
- Builds modular integration layers with clean contracts
- Fixed roadmap in week 2, code starts week 3
- Fixed price quote, no hourly surprises
- HIPAA, SOC 2, and PCI-DSS ready from day one
- CI/CD for models, monitoring, and rollbacks built in
4 phases to AI integration
Our fixed process connects AI to your software on a predictable timeline.
We don't start coding until we understand your data. In the Idea phase (week 1-2), we audit your APIs, schemas, and compliance requirements. The Roadmap phase ends with a fixed-price quote and a clickable prototype of the integration architecture.
From there, Product phase runs 6-10 weeks, with weekly demos. Release is the final week, where we deploy to your environment, run load tests, and hand over documentation. 98% of our projects ship on time because the integration boundary is clear from day one.
What ships with your AI integration
Every IRPR integration includes the code, configs, and artifacts to run in production from day one.
You don't get a proof-of-concept. You get a production-grade module ready for your DevOps team to manage. We deliver a Dockerized service with your CI/CD pipeline of choice, monitored by Sentry, and documented with Swagger. No black boxes.
- Modular Python/FastAPI or Node.js integration service
- Docker container with multi-stage build
- CI/CD pipeline on GitHub Actions or GitLab CI
- Model endpoint for GPT-4, Claude, or Hugging Face
- API documentation with Swagger/OpenAPI spec
- Sentry error tracking and alerting
- Monitoring dashboards in Grafana or Datadog
- Data encryption at rest and in transit (AES-256, TLS 1.3)
- Load testing scripts with k6
- Source code committed to your repository
What we ship in this practice.
AI document classification for a law firm
Reduced manual document sorting by 15 hours per week. Used AWS Comprehend for entity recognition, FastAPI for the integration layer, and MongoDB for metadata storage. Deployed on the firm's private cloud with SAML authentication.
Chatbot for a SaaS support team
Cut first-response time by 60%. GPT-4 model exposed via a Slack bot, pulling context from the company's existing Zendesk API and PostgreSQL knowledge base. Dockerized service on Kubernetes.
Predictive maintenance for a manufacturer
Reduced unplanned downtime by 25%. PyTorch model trained on sensor data from AWS IoT Core, with inference results written back to the plant's OSIsoft PI system via a custom connector.
Lead scoring for a real estate CRM
Increased conversion rate by 30%. XGBoost model fed by Salesforce streaming API and MLS data, retrained weekly on Databricks. Results surfaced in the existing agent dashboard.
Clinical trial matching for health tech
Matched patients to trials 2x faster. Python service queried a Snowflake data warehouse and an IRB-approved protocol database, using a BERT-based NLP model. Deployed in a HIPAA-compliant VPC.
Inventory forecasting for an ecommerce brand
Reduced overstock by 20%. TensorFlow model consumed Shopify order data via webhooks and Google BigQuery analytics, outputting daily restock suggestions to the warehouse management system.
Why teams hire us.
We integrate, not rebuild
IRPR connects AI to your existing Postgres, MySQL, or MongoDB databases and your REST/SOAP APIs. No need to migrate or re-platform. We've done this for 200+ products.
Fixed price, no surprises
Every AI integration project gets a fixed quote in the Roadmap phase (week 2). No hourly billing, no scope creep charges. The price is the price.
8-12 week delivery
From roadmap sign-off to production deployment, we ship in 8-12 weeks. Our average on-time rate across 200+ projects is 98%.
Compliance built in
We handle HIPAA, SOC 2, and PCI-DSS requirements from day one. Your AI will process sensitive data with encryption, audit logs, and access controls.
You own the code
All code, models, and documentation go into your repository. No lock-in, no proprietary runtimes. Full IP transfer upon final payment.
Senior engineers only
Our team averages 8+ years of experience. No juniors, no outsourcing. Every engineer has shipped AI integrations with Python, Docker, and cloud services.
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.