My internship experience: Turbine, mentorship, and the freedom to explore

Recent Impira engineering intern, Alex Tarng, shares about his summer experience with Impira as he worked alongside our engineers and chief architect to dig into real engineering solutions, implement his own ideas, and see his work be deployed and utilized.

Michael Andrews, Impira’s co-founder and chief architect, talks through solving machine learning problems, implementing incremental execution, and how his team works through new ideas and tackles big challenges.

To err may be human, but when it comes to data entry, why not free people up to do things people do well, like being creative, strategic, and bold? Let’s leave the computer work to computers, and let humans be more human.

Amy Le tells us how several collaborative teams at Impira combined their efforts to create the Review Workflow — a new way of reviewing machine learning predictions that’s quicker and less tedious.

The old ways aren’t always better. Just like white-out is a thing of the past and my old Nokia brick is now a fond and very distant memory, manual data entry also needs to be wiped out of our norm of day-to-day work.

Our CEO, Ankur Goyal, joined the folks at CMU Tech & Entrepreneurship for a virtual chat about his journey, Impira’s evolution, and his insights on the AI/ML landscape. Watch the video or read through some of the highlights.

From small businesses to enterprises — you’re either getting ahead or falling behind. Take leaps and bounds in your digital transformation journey by automating your major business processes and everything in between.

At Impira, we’re driven by the goal of removing repetitive manual tasks that hamper productivity and keep your teams from focusing on more important work. We’re always on the lookout to integrate with other like-minded solutions if it’ll give our users more opportunities to save themselves from data entry dread.

It’s no secret that businesses can use machine learning (ML) to drive automation across various processes. Most orgs are either building ML models from scratch or implementing pretrained models. These options are both time consuming and costly, but there’s a third option: A platform you can customize without any coding knowledge.

We’re always listening and looking for ways to be there for users. In responding to feedback, we’re committed to being hands on so you can be hands off with manual work.