AI Integration

AI connected to the systems you run on.

AI is only useful when it can reach the records your business depends on and return its work to the right place. Metacto engineers the integrations that connect AI to your CRM, ERP, documents, ticketing, and email, securely and reliably.

45 minutes with our AI experts to find your highest-value opportunity and a practical next step. No preparation required.

Talk to an expert Explore AI Implementation

For teams whose AI pilots work in isolation but stop short of the systems where the business actually records and decides.

When integration is the missing piece

Most AI pilots stall at the edge of the systems of record. The model works. The connection does not.

Outputs stop at a copy and paste

AI produces a useful draft, then a person moves it into the CRM, ticket, or record by hand.

Access is all or nothing

The AI either cannot see the data it needs or sees far more than the task requires.

Failures go unnoticed

A timeout or a changed field breaks the connection, and nobody knows until the work is missing.

A new tool nobody opens

Teams are asked to work in a separate AI interface instead of the tools they use every day.

What Metacto builds

Each integration element is paired with the business reason it exists.

System connectors: CRMs, ERPs, document stores, ticketing, and email, so AI works from current records.
Read and write separation: read access to inform the work, write access only where an action is approved.
Write-back to systems of record: results land in the record your team already trusts, not a side channel.
Authentication and secrets: credentials stored and rotated securely, never placed in prompts or code.
Failure handling and retries: timeouts, rate limits, and partial failures are caught, retried, or escalated.
Data mapping and validation: fields are checked before anything is written, so records stay clean.
In-tool delivery: AI output appears inside the tools teams already use, where the work happens.
Change awareness: integrations are monitored for upstream changes that would break them.

How integrations are built and tested

Each integration is designed from the access it needs, built against your real systems, and tested for failure as well as success.

01Design

Map systems and access

We identify the systems involved, the records each task reads and writes, and the minimum access required for each connection.

An integration plan your IT and security owners can review before work begins.

02Build

Build connections and write-back

We implement the connectors, authentication, data mapping, and write-back paths, inside the tools your team already uses.

AI reading from and returning work to your systems of record in a controlled setting.

03Prove

Test for failure, then launch

We test real cases alongside failure scenarios such as timeouts, permission errors, and changed fields, then confirm results with your team.

Integrations in use with documented behavior when something goes wrong.

Example: what an integration map covers (illustrative)

A simplified outline of the integration map we agree on before building. Shown for illustration, not taken from a client engagement.

Systems in scope: each application, its owner, and the environment it runs in
Records and fields: what the AI reads and what it is permitted to change
Access model: read and write permissions per connection, and who grants them
Authentication: how credentials are issued, stored, and rotated
Write-back rules: when results are written, and which require approval first
Failure behavior: retries, fallbacks, and who is notified when a connection fails
Validation checks: what is verified before any record is updated
Test cases: the real scenarios used to confirm the integration before launch

Controls

Integrations your security team can approve

Access, credentials, and write-back are designed with your IT and security owners from the start.

Access

Least privilege by default

Read and write access granted separately
Scoped to the records each task requires
Credentials kept out of prompts and code

Write-back

Changes you can trust

Validation before any record is updated
Approval steps for consequential changes
Logged writes your team can review

Reliability

Built to handle failure

Retries and fallbacks for transient errors
Alerts when a connection stops working
Monitoring for upstream system changes

We confirm systems, access, and data handling with your IT and security owners before any connection is made.

Common questions

Which systems can you connect AI to?

CRMs, ERPs, document stores, ticketing systems, email, and internal databases are the most common. If a system exposes an API or a reliable export, it can usually be connected. We confirm feasibility for each system during planning.

Does AI get write access to our systems?

Only where a task requires it and you approve it. Most integrations start read-only. Write-back is added per action, with validation before any record changes and approval steps for consequential updates.

How do you handle credentials and secrets?

Credentials are stored in a secrets manager, scoped to each connection, and never placed in prompts or application code. We follow your existing identity and access policies where they apply.

What happens when an integration fails?

Each integration has defined failure behavior. Transient errors are retried, persistent failures are escalated to an owner, and no partial or invalid data is written to your systems of record.

Will our team need to use a new tool?

Usually not. We prefer to deliver AI output inside the tools your team already uses, such as the CRM, the ticketing system, or email, so adoption does not depend on a new habit. Systems can also run on Vocion, Metacto's open-source operating layer.

Which service includes this capability?

AI Implementation is where most clients put this capability to work, as part of putting one system into production. Custom AI Development and Managed AI Services also depend on it.