# Enterprise AI Integration Services

> Connect AI capabilities to the systems your business already uses. Integration work covers the operational path from data and identity to deployment, monitoring and controlled rollout.

[Read the full service page](https://www.g-atai.com/enterprise-ai-integration)

## When this service fits

This service fits teams with a model or pilot that needs to work inside existing applications, or businesses adding AI to an established software stack. Dependencies and access controls matter as much as the model.

## What we scope and deliver

- Integration architecture covering APIs, data contracts, identity and access boundaries.
- Serving or orchestration interfaces with logging, versioning and error handling.
- Deployment plan, monitoring checks and rollback procedures for a staged rollout.

## How success is evaluated

Validate the full workflow in a representative environment. Check permission boundaries, data quality, latency, failure recovery and operating costs. Security and compliance requirements are scoped with your team rather than implied by the use of AI.

## What to bring to the first call

- System architecture, API documentation and deployment environments.
- Identity, data handling and network requirements from your technical team.
- The current pilot, expected traffic and operational ownership.

## From discovery to delivery

### Define the business problem

Map users, the current workflow, data access and constraints. Agree on the baseline, acceptance criteria and scope before choosing a model or committing to a build.

### Test a focused pilot

Evaluate a representative task with your data and users. Check quality, error handling, latency and running costs before expanding access or automating critical decisions.

### Integrate and hand over

Plan permissions, deployment, monitoring and human review with your team. Agree on documentation, training and ongoing support in the project scope.

## Before you start

### How much does an AI project cost?

Pricing depends on the workflow, data readiness, integrations, security requirements and support scope. A strategy call helps define these inputs; a proposal should separate implementation work from model, cloud and third-party running costs.

### Can we start with our existing software?

Yes. The first step is to assess available APIs, permissions and data access. A limited integration or pilot may be more suitable than replacing a working system. Feasibility and delivery dates are agreed after discovery.

### Will AI operate without human review?

That depends on the risk and task. Define approval points, permissions, fallback behavior and audit logs before deployment. Sensitive actions should stay within the controls agreed with your team.

## Explore related project work

These project pages show capabilities and product concepts. They do not establish independently verified customer outcomes or promise a return on investment. GARC includes a floor-plan beta; LogiTwin is a logistics concept.

- [FinSight AI](https://www.g-atai.com/finsight)
- [MediVerse](https://www.g-atai.com/mediverse)

## Plan your implementation

Share your workflow, current systems and target outcome. Choose a time for a strategy call to discuss feasibility, scope and the next step.

- [Book a strategy call](https://www.g-atai.com/booking/build-ai)

## Technical services

- [AI Integration & Scalable Deployment](https://www.g-atai.com/ai-deployment)
- [Data Engineering for Production AI](https://www.g-atai.com/data-engineering)
- [AI Consulting Services](https://www.g-atai.com/ai-consulting)
- [AI Agent Development Services](https://www.g-atai.com/ai-agent-development)
- [AI Business Automation Services](https://www.g-atai.com/business-automation)
- [Custom AI Development Services](https://www.g-atai.com/custom-ai-development)
- [Intelligent Software Development Services](https://www.g-atai.com/intelligent-software-solutions)