AI system integration and custom development

For Your Business

Who this service is for and when to start

When employees can already use AI to complete part of their work but still need to repeatedly export files, copy content, and fill in fields, connections to existing systems can be considered. Integration requirements that may be discussed include querying cases, generating drafts for approval, or returning extracted document results to business processes.

Before implementation, it is advisable to confirm whether tasks are stable and whether inputs, outputs, and approvers are clear. If manual processes are not yet determined, rules should be organized first; if system interfaces are managed by external vendors, it is necessary to confirm interfacing permissions and cooperation methods in advance.

The Challenge

Common challenges faced by businesses

Different systems may use different customer numbers, date formats, and status definitions. For example, 'closed deal' in CRM does not necessarily mean it has been recorded in the financial system. If the meaning of fields is not clarified before integration, the response may appear reasonable, but the actual write-back may still fall into incorrect records.

Another challenge is how to continue after a failure. Request timeouts do not mean the backend has not completed; resubmitting may result in duplicate work orders or data changes. A test environment working normally does not guarantee the same performance under production load, and rate limiting, permissions, platform failures, and maintenance windows must also be considered.

Our Approach

Methods and applicable requirements

Define Data Flow and System Responsibilities First

Identify the authoritative source, query scope, transformation rules, and write destination for each piece of data. AI can assist in interpreting text or providing results, but business fields, required conditions, and acceptable values should be validated by the application. Operations that require traceability should retain appropriate request identifiers and result records.

Separate Model Suggestions from Actual Execution

After the model proposes a query or operation request, it needs to be further processed by the application or service responsible for execution. For enterprise-built interfaces, making a tool call does not mean the operation is authorized or successfully executed; the execution result and business status must still be checked.

We recommend that the backend checks identity, parameters, and business conditions, and then executes according to the approved scope. Operations such as writing, deleting, or submitting external information should have confirmation and recording arranged according to the impact level; the permissions provided by the system are limited to what is required for the task.

Arrange retries and exception handling

Submitting the same request repeatedly may cause duplicate entries or altered data. When implementing, it is necessary to distinguish between temporary failures and non-retriable errors, design duplicate request identification, limited retries, and manual verification.

Idempotency means that repeating the same operation still produces the same effect. For example, creating a record can use business identifiers and processing status to avoid duplicate additions; the actual method depends on the original system's capability. If the result cannot be confirmed, it should first be marked for verification, and follow-up processing should be arranged.

Preparation

What documents do companies need to prepare?

• System interface: System name, API or import/export documents, authorization limitations, and vendor contact point.
• Data rules: Field definitions, source and destination, identifiers, and acceptable input/output examples.
• Environment permissions: Test environment, required roles, deployment constraints and data-retention requirements. Production credentials are not needed for an initial discussion.
• Acceptance scenarios: Normal and exceptional cases, manual approval steps, business managers, and expected usage.

Project Planning

Estimating time and cost

The number of systems, interface completeness, data differences, custom screens, permissions, and deployment restrictions all affect workload. Whether the manufacturer provides a test environment, supports necessary fields, and whether interface changes need to be scheduled separately should also be evaluated.

Confirm implementation, third-party licences, model and cloud usage, monitoring and maintenance costs separately. A prototype can validate one data flow. Complete acceptance checks, permissions and maintenance arrangements before production use. Record responsibility for source code, deployment accounts and future changes in the agreed scope.