Capture Institutional Knowledge

Win back your time and give your team the ability to effectively collaborate with an intuitive telemetry stack.

Sift implements more fault tolerant processes and speeds up data review, while capturing your metadata and comments in a single, searchable source of truth. You can simplify your data review workflow and share previously siloed tasks with a system designed to help you innovate and scale.

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  1. Assign annotations to your team members as you review the data.
  2. Collaborate in the comments and during test campaign workflows.
  3. Quickly search through historical data to speed up investigations.

Housing institutional knowledge in-line with your data

Sift is a telemetry stack that’s designed to help machine creators innovate, scale, and operate smoother and faster. Where legacy systems typically make it difficult to keep your knowledge current and accessible, Sift allows you to access and utilize data without getting bogged down — giving you more time to focus on your vision.

How does it work?

Right now, you might be wading through a labor-intensive data review process — one that requires searching through emails, documents, and layers of design reviews to access the information you need. And there may be only one or two people on your team who can even understand your telemetry dashboard.

This arduous process strangles innovation and eats up your time. It also leaves too much risk for error and attrition. Sift houses your institutional knowledge in-line with your data, giving you direct and searchable access to it. You’ll no longer have to solely rely on a few staff members with specialized knowledge. Inspired by the same processes used to launch human-rated spacecraft, Sift allows you to securely share all your machine performance data with the right people, so that you can collaborate on previously siloed investigations. You can save time, collaborate, and quickly address problems — all within an intuitive platform.

Sift makes convoluted data review processes straightforward and streamlined, with built-in rules similar to code. The software analyzes your data continuously and alerts you to off-nominal behaviors — eliminating tedious hours spent staring at lines on hundreds of dashboards. Sift also captures comments on annotations, automatically creating and refreshing documentation so it never goes stale. And with Sift’s query optimized search, you can quickly look through historical data spanning back years — all without contacting IT to pull up archives. It’s important to note here that you must be mindful about documenting other parts of your process for official purposes. But with Sift, your actions and discussions are immediately saved for later reference.

When you’re finished with your investigations, your findings will live in Sift alongside all of your data. This enables future engineers to solve problems with complete contextual understanding, removing a major source of “Key Engineer Risk.” What this means is you can scale your infrastructure and empower more of your team to contribute to the review process, getting to market faster. It gives you the ability to find everything in one organized place, reducing overall software costs, not to mention wasted time and staff burnout.

Streamline your data review process and reduce time spent on investigations with Sift’s intuitive telemetry stack.

Commonly asked questions

Will this eliminate the need for word documentation?

While you will likely still need to document other parts of your process for official purposes, no official documentation is required to record your actions, decisions, and collaboration in Sift. Just as Email and Slack serve two separate functions in corporate communication, Sift and Confluence serve each of their functions particularly well.

Will this create the “too many platforms” problem for my team between Jira and Sift?

Sift will actually optimize the way you use your platforms. You’ll reduce your noise in Jira — where data isn’t easily searchable. Your institutional knowledge will be stored in Sift where it will work in line with your data while Jira tracks downstream actions.

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