CTERA Introduces Forward Deployed Engineering to Close the AI Skills Gap and Accelerate Enterprise Deployments

CTERA, a reference in intelligent data management, announced CTERA Forward Deployed Engineering, a new service that places CTERA engineers inside customer environments to operationalize specific AI use cases in production on the organization’s own unstructured data.Each engagement is tied to a defined business outcome, works against real enterprise file data, and is designed to leave the customer’s team able to run and extend what was built.

Most enterprises now have access to capable AI models and tools. Far fewer have AI delivering reliable results in production. Futurum’s 1H 2026 data intelligence decision maker survey of 818 data leaders found that a shortage of specialized talent is the fastest-rising factor behind AI project failures, and that the organizational challenge insufficient skills and expertise more than doubled in six months.

The challenge is sharpest with unstructured file data, where much of an organization’s knowledge lives. File data estates built up over decades are often duplicated, stale, and inconsistently permissioned. Pointing AI at that data without proper preparation can produce confident but wrong answers, or surface information to people who should not see it. Both outcomes erode the trust AI initiatives depend on.

How CTERA Forward Deployed Engineering Works
Small, dedicated teams, pairing a Forward Deployed Engineer and Deployment Strategist, work as part of the customer’s project teams, with access to the environments and to the subject-matter experts who know how work actually gets done in an organization. Engagements follow a phased approach with discovery and data grounding, a first production use case, scaling across additional workflows, and handover for independent operation.

Key elements include:

• Start from the data. CTERA engineers assess the real file estate, including volumes, access patterns, and source systems, to validate use case workflows with data evidence
• Prepare data AI can use safely. The team identifies which data sets a workflow needs, then classifies, organizes, and governs them in place. AI works only with content each user is already authorized to access
• Build into existing workflows. Workflows integrate with the systems and AI tools the organization already uses through open standards such as the Model Context Protocol and automation platforms, such as n8n, and are validated against real data before go-live
• Transfer ownership. Customer engineers work alongside CTERA from the first phase, and document configuration as they build it. An engagement is complete when the customer can add the next use case without CTERA

Forward Deployed Engineering builds on the CTERA Intelligent Data Platform, which provides AI-governed access to enterprise file data across edge locations, data centers, and cloud environments without moving it.

“Enterprises aren’t short of AI tools. What they’re short of is the time and specialized skills to connect those tools to their own data and workflows safely,” said Oded Nagel, CEO, CTERA. “Forward Deployed Engineering puts our engineers alongside customer teams to do that work, get a real use case into production, and leave the customer able to run it themselves.”

Availability
CTERA Forward Deployed Engineering is available now for organizations using the CTERA Intelligent Data Platform. Engagements can be structured flexibly based on time or as fixed-scope projects with milestone-based acceptance criteria.