The data plumbing behind your AI, kept running.
Private AI is only as current as the data feeding it. Managed Data Infrastructure covers connectors, synchronization, pipelines, and the PostgreSQL and storage behind them, including the permission syncs that keep retrieval honest.
Pipelines fail quietly.
A source system changes a schema, a credential expires, a file share is reorganized, or a sync job starts running longer than its window. Nothing alerts; the AI keeps answering from stale or incomplete data, and permissions drift from the source. Users notice weeks later, if at all.
Managed Data Infrastructure treats freshness and permission accuracy as operated properties with monitoring and runbooks, not as one-time integration work.
What we operate.
Connectors
Credentials, connectivity, and version updates for databases, documents, and business applications.
Synchronization
Schedules and change capture tuned to each source's load and freshness needs.
Permission sync
ACL and group syncs monitored so retrieval reflects current source access.
Schema changes
Detection of upstream changes and coordinated updates to mappings and classification.
Databases
PostgreSQL and pgvector operations: tuning, maintenance, storage growth, and replication.
Lineage
Pipeline changes recorded so data lineage stays accurate.
Signals that predict problems.
| Signal | What it can indicate | Typical response |
|---|---|---|
| Sync lag | Source slowdowns or job contention | Reschedule, tune, or add capacity |
| Error rate per connector | Expired credentials, API changes | Rotate credentials or update connector |
| Row and document counts | Silent truncation or deletions | Investigate before re-index |
| Permission sync age | Retrieval using outdated ACLs | Prioritize the sync, alert owners |
| Index and table growth | Storage pressure ahead | Capacity plan or archive |
Taking over existing pipelines.
- 1
Inventory
Document sources, schedules, owners, and current failure history.
- 2
Instrument
Add freshness, error, and permission-sync monitoring where missing.
- 3
Stabilize
Fix recurring failures and document runbooks for each source.
- 4
Operate
Ongoing operations with regular freshness and incident reporting.
Source owners, your data team, and Data.co.
Data infrastructure has an extra party compared with other managed services: the owners of each source system. The matrix makes their role explicit.
| Activity | Source system owner | Your data team | Data.co |
|---|---|---|---|
| Read access for a connector | Grants a read-only account | Requests and tracks it | Stores it as a secret reference and rotates on schedule |
| Schema or API change upstream | Announces where possible | Decides on new mappings | Detects, proposes, and applies the change |
| Classification of new fields | Advises on meaning | Approves labels | Flags unlabeled fields and runs the pipeline |
| Sync schedule | Sets load limits | Sets freshness targets | Tunes jobs to fit both |
| Incidents | Fixes source outages | Communicates impact to users | Detects, triages, and recovers pipelines |
A credential expires overnight.
The document-management connector starts returning authentication errors at 2 a.m. The error-rate alert fires, and the engineer on duty confirms the cause from the connector log rather than guessing. The runbook says what happens next: the credential belongs to the source owner, so we open a rotation request with them through your ticketing process, pause the sync so it stops retrying against a locked account, and mark the collection as stale in reporting.
Retrieval keeps serving the last good index, with its permissions as of the last successful sync. If permission sync age crosses the target you set for that source, the policy you chose applies: some teams accept slightly stale access for a short period, others restrict the collection until the sync catches up. Once the new credential is in place, the sync resumes, counts are checked against the source, and the incident record closes with a note on the rotation date so it is renewed before expiry next time.
Questions buyers ask
Do you own our source systems too?
No. Source systems stay with their owners. We operate the connectors and pipelines that read from them, within the access those owners grant.
How quickly do permission changes reach retrieval?
It depends on the source and the sync schedule you choose. We monitor permission sync age and alert when it falls behind the target set for each source.
Can you manage pipelines that do not feed AI?
The service is focused on data feeding Data.co Control. Adjacent pipelines can be included where they share infrastructure, as scoped in the contract.
Who decides how data is classified?
Your team owns classification rules and labels. We operate the classification pipeline and flag new fields or sources that need a decision.
Do connectors write to our source systems?
Connectors are read-only by default. Any write path is configured explicitly, governed by policy, and listed in the contract scope so it is never a side effect of routine operations.
See it against your own use case.
A 30-minute technical walkthrough, policy simulation on your scenarios, and a deployment recommendation for on-prem, private cloud, or hybrid.