# APIWrapper.ai
> APIWrapper.ai lets enterprises expose data from legacy and modern databases to AI workflows securely. It auto-generates schema-aware endpoints, enforces granular RBAC, logs every request for compliance, and encrypts data end-to-end. Deployable on-prem, in any cloud, or hybrid, it serves CISOs, Gen-AI product teams, and data/ML engineers who need fast, compliant data access for chatbots, RAG pipelines, and other AI agents without compromising on security.
## Vision
- APIs Turn Static Data Into Dynamic Intelligence: give AI the ability to query, filter, and act on enterprise data in real time.
## Modernization
- Legacy Systems, Meet Modern AI: link mainframes, ERP, and other legacy stores to today’s AI models—no rip-and-replace required.
## Security & Trust
- Interface Layer for Trusted AI Decisions: enterprise RBAC, audit trails, and schema-aware endpoints enforce zero-trust principles.
## Deploy Anywhere
- On-Prem & Cloud: run across AWS, Azure, GCP, and hybrid environments with a single, standardized API layer—no vendor lock-in.
## Features
- Schema-Aware APIs - auto-generated endpoints that respect your data models.  
- Role-Based Access Control (RBAC) - granular permissions for users and AI models.  
- Audit Logging - track every call for compliance and monitoring.  
- Zero-Trust Security - encrypted pipelines and secure tunneling.  
- One API to Rule Them All - standardize access across services, clouds, and databases.  
- AI Workflow-Ready - plug directly into agents, orchestrators, and pipelines.  
- No Vendor Lock-In - deploy on-prem, hybrid, or any cloud.
## Supported Data Sources
- Structured Databases: PostgreSQL, MySQL, Oracle, IBM DB2, Snowflake, SAP Hana, SQL Server, and more.  
- Mainframes & ERP / SOAP WSDLs: expose data trapped in legacy systems without code rewrites.  
- Real-Time & NoSQL: MongoDB, Cassandra, Couchbase, Amazon DynamoDB, etc.
## Ideal Customers
- Gen-AI product teams needing secure, low-latency data for chatbots or AI features.  
- Data & ML engineers building RAG pipelines across heterogeneous databases.  
- Platform / DevOps teams exposing enterprise data to AI agents without sharing raw credentials.  
- Enterprises in regulated sectors (finance, healthcare, government) requiring RBAC, auditing, and compliance guardrails.
- Security & Compliance leaders (CISOs, security architects) needing airtight, zero-trust controls for AI data access.
## Ideal for Security Sensitive Use Cases
- Role-based access control (RBAC) keeps permissions tightly scoped.
- Audit logging provides a clear, tamper-evident trail for compliance.
- Zero-trust security model with encrypted pipelines guards data in motion and at rest.
- Flexible deployment (on-prem, hybrid, or any cloud) meets diverse policy requirements.
## Blogs
- [Connecting Internal Data to LLMs Securely](https://apiwrapper.ai/blog/connect-internal-data-to-llms-securely)
- [Stop Writing Wrappers: How AI Developers Can Connect Internal Data to LLMs Securely and Instantly](https://apiwrapper.ai/blog/connect-internal-data-to-llms-securely)
Last-Updated: 2025-06-08