AI You Can Trust: TimeXtender's Biggest Release Yet

TimeXtender turns 20 this year. This is the biggest release we've ever shipped.

Right now, every data vendor has an AI story. Most of them look the same: a natural language interface, a confident answer in seconds, a demo that lands well. What happens after the demo is a different story. The AI picks the wrong revenue field. It misses a filter Finance always applies. Someone catches it, trust breaks, and the tool gets quietly shelved.

The problem isn't the model. It's that the model has no idea what "revenue" means in your organization. It's guessing. And in production, guessing isn't good enough.

What AI needs to produce answers worth acting on is governed context. The same approved definitions your analysts have validated. The same ones powering your dashboards and board reports. When AI works from that foundation, the answers are consistent, traceable, and reliable enough to act on.

We've spent 20 years building that foundation. That's what this release is built to deliver. 

Introducing Xpilot Analytics

Self-service BI has promised the same thing for a decade: business users should be able to get answers without depending on an analyst. The tools improved. The dependency never really went away. Someone still had to build the dashboard. The queue never fully emptied.

Xpilot Analytics changes that.

Starting today, Xpilot Analytics is available in Private Preview inside the TimeXtender Data Platform.

With Xpilot Analytics, a user types a question in plain language, the system queries their governed semantic model, and an answer streams back in seconds with charts and tables rendered inline. No SQL. No report designer. No ticket to file.

What makes this different is what sits underneath it. Xpilot doesn't guess at what "revenue" means. It queries the semantic model your data team has already built and validated, the same one powering your dashboards and board reports.

• Transparent queries — view the exact SQL executed, see reasoning steps, inspect tool calls
• Pinned dashboards — pin any result to a live dashboard that re-executes against the data warehouse on demand
• Persistent conversations — sessions save across logins; export any result to CSV, image, or Markdown
• AI governance — all AI calls route through a governed intermediary; European data residency enforced; per-user access controlled by org config

Xpilot Analytics is in Private Preview now, with general availability targeted for early H2 2026. Sign up for early access here: https://www.timextender.com/en-gb/get-early-access-timextender-xpilot-mcp

TimeXtender MCP Server

Xpilot Analytics is built on the same governed semantic layer that powers the improved TimeXtender MCP Server.

If your team is already using Claude, ChatGPT, Copilot, or a custom AI agent, TimeXtender MCP Server lets those tools query your data the same way, through the governed definitions your analysts trust, not raw schema inference.

MCP Server 2.0 is now in Public Preview. Key changes in this release:

• Single server, multiple models — one install, one config file, one Windows service hosts as many semantic models as configured
• OAuth authentication — ChatGPT and other LLMs can now connect via custom connectors
• Cloud relay tunnel — on-prem data is reachable by AI tools without opening firewall ports
• Snowflake and Fabric endpoint support — both now fully supported alongside Azure SQL, with native SQL dialect handling for each

MCP Server is included at no additional cost as a Deliver endpoint in TimeXtender Data Integration.

Microsoft Fabric: The Biggest Leap Yet

Microsoft Fabric has been one of the most talked-about data platform investments of the last two years. It has also been one of the most challenging to run with confidence. Teams adopting Fabric have run into real limitations: missing view support, data type inconsistencies, parallel execution issues, and gaps that made it hard to fully commit.

This release takes the biggest step forward we've made on Fabric to date.

TDI 7359.1 ships 16 Fabric Lakehouse improvements, including materialized and persisted views, more reliable data type handling, parallel execution support, and a storage cleanup tool. These aren't cosmetic fixes. They close the gaps that have been blocking real-world Fabric deployments, and we're eager to see how partners and customers put them to work.

Also shipping in this release: Fabric Warehouse enters Public Preview as a first-class Prepare storage option inside TimeXtender, pairing with Fabric Lakehouse for Ingest in the same workspace. Full Fabric Warehouse support beyond simple mode is targeted for Q3 2026.

If your team is building on Fabric, now is the time to get a project underway. The improvements in this release are significant, and your feedback is exactly what moves this from preview to GA.

Snowflake Feature Parity Complete

This release closes the book on Snowflake feature parity:

• Snowflake on AWS — supported for both Ingest and Prepare; no need to cross clouds to stay in-region
• Object-level security — closes the last meaningful gap with SQL Server
• MCP Configurator support — AI agents can now query Snowflake-backed semantic models

Teams that have been waiting for Snowflake support to mature before committing to a full TimeXtender deployment no longer have a reason to wait.

A New Home for Everything

This release also marks a significant change to the platform itself. TimeXtender Turnkey is now the TimeXtender Data Platform. The rename reflects something that has been true for a while: TDP is no longer a standalone product sitting alongside the rest of the TimeXtender stack. It's the unified home for all of it.

What's new in TDP 26.2:

• Dark mode — the single most-requested UI item from customers
• Refreshed UI — updated workspace icons, reworked workspace switcher, new component library for consistent look and feel across all modules
• Recent Executions grid — at-a-glance view of what ran, what succeeded, and what needs attention, right from the Dashboard
• Orchestration API v1 — trigger jobs and query logs programmatically
• Data Enrichment embedded — accessible directly inside TDP with a single login
• User Roles with Entra ID group support — cleaner access control across the platform
• Dataset Health Scores and TDI Environment-Aware Sync

The direction here is straightforward: one modern, web-based experience for the full data pipeline, from ingestion through to AI-ready delivery.

The Foundation Under Everything

Every capability in this release sits on top of a data pipeline that has to work reliably. The last update in this release is about making sure it does:

• Streaming file loads — file sources rebuilt from the ground up; multi-GB Parquet, CSV, XML, and JSON no longer crash mid-execution or require manual splitting before ingestion
• Incremental loading — now works reliably across S3, GCS, Azure Blob/ADLS, SharePoint, and OneDrive; large file-based pipelines no longer need a full reload every time something changes
• MySQL — fully refreshed provider with SSL/TLS support and proper localization handling, addressing compatibility issues that affected international deployments
• MongoDB — moves to production-ready status after an extended preview period
• Business Central — plugin fully refreshed, improving reliability for customers running Microsoft ERP pipelines
• Metadata Manager — full in-grid configuration now supported, closing a long-standing workflow gap that previously required jumping between screens to complete basic setup
• Qlik Cloud spaces — Deliver endpoint now supports Qlik Cloud spaces, aligning with how Qlik manages Dev and Prod environments
• Ingest reliability — a range of fixes across data sources and ingest pipelines, including improved handling for incremental loads, primary key updates, and large data area deletions

Next Steps

• Sign up for early access (MCP Server and XPilot Analytics previews): https://www.timextender.com/en-gb/get-early-access-timextender-xpilot-mcp
• Request a demo: https://www.timextender.com/en/request-a-timextender-demonstration

• Contact Sales: https://www.timextender.com/en/lets-talk