Your Time is Now: Prepare for the Next Peak Season

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As retailers battle through the remainder of this year’s holiday peak season, there’s one question I consistently hear across the board from all retailers: How do we stay competitive and deliver a delightful customer experience that keeps them coming back again and again? After having experienced 13 holiday seasons throughout my career, the answer lies in speed and accuracy.


So how can you prepare for the next peak season? First step – start now! Second, AI powered robotics are a must if you want to remain relevant. Here are three things to start now to prepare for the next peak:


1. Reduce the Burden of the Staffing Shortage  

AI powered robotics make your processes more efficient and require less manpower in your distribution centers. One robot has the potential to fill several employee shifts, allowing you to level-up your workers’ skills and hire less people during peak season.


As an example, our  customer Gap, Inc., uses robots to sort items at its distribution center in Gallatin, Tenn. In previous years, the company had to increase its human workforce by six times to keep up with demand during peak seasons. After putting robotics in place, they now require much less workforce ramp up during peak periods.  

2. Fulfill Orders More Quickly

End-consumer happiness is a KPI for online retailers and it starts on the warehouse floor. With some major retailers offering same-day or two-day shipping options, the pressure is on to fulfill orders quickly.


The reality is that humans get sick, they need breaks, they can’t work 24 hours straight and unfortunately, they quit. The beauty of robots is that they constantly work at a consistent pace without a shift change, distraction, taking breaks or falling ill, which helps you meet your throughput goals. Robots provide consistent output, and in turn, faster order fulfillment. That can be the difference between a bad review and a happy customer.

3. Increase Order Accuracy

According to one survey of 300 supply chain and distribution managers, fulfillment centers across the U.S. lose an average of $585,000 per year due to mis-picks. While humans are the most accurate workers, mistakes happen when employees are assigned to mundane, repetitive tasks such as picking. Robots with AI combined with automated scanning capabilities guarantee that product data and order fulfillment is accurate.

Now is the time to prepare for the next peak season to delight your customers to drive repeat purchases. Using intelligent robotic technologies, you can grow your operations as demand increases, create a dynamic workforce that marries automation with human skills, and increase throughput and accuracy.  We’re here to help!

Interview with Anurag Maunder, SVP of Engineering at Kindred.ai

Check out our latest interview with our SVP of Engineering, Anurag Maunder, where he shares advice on how to navigate a career in engineering.

 
  Location:  San Francisco, CA  Current Role:  SVP of Engineering at Kindred.ai

Location: San Francisco, CA
Current Role: SVP of Engineering at Kindred.ai

 

MANAGERS CLUB (NOV 2018)

What’s your background and how did you get into management?

I did my Ph.D. in Computer Networking and joined Bell Labs. After a few years, I realized that I have a lot of passion for building products. This took me to Bay Area. Becoming a manager was quite organic. I proposed a project and was soon leading a team of engineers as a Tech Lead. I did this for a couple of years till the line between being a Tech Lead and Manager blurred!

When I started my own company, I had the responsibility for building the first product which organically translated into VP of engineering. I enjoyed the job ever since and I often switch between CTO and VP Engineering role on as needed basis!!

What are the biggest challenges you face?

One of the biggest challenges I face is hiring. It requires sustained effort to source and bring on the right talent to help drive our research and product development forward. Once we’ve onboarded any new candidate, it is important to get on the same page about team and company-wide goals. Right out of the gate, we need to be aligned so that we’re all marching toward the same objectives across teams.

At Kindred, we’re driven by results. We want our team members to aim for personal and professional progress and feel that individual excellence deserves to be recognized. We celebrate both individual and team wins, but also know how important it is for our people to maintain healthy work-life balance. As a manager, it’s important to me that my team is happy and fulfilled and I believe this balance, in turn, cultivates a strong collective work ethic.

Read the full interview here

Kindred introduces SenseAct, the first reinforcement learning open-source toolkit for physical robots

 
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BUSINESS WIRE (SEP 2018) - Kindred, an AI and robotics company that builds intelligence for robots, has announced today the launch of SenseAct, the first open-source toolkit to set-up reinforcement learning tasks on physical robots. Kindred’s SenseAct was created to provide robotics developers and researchers with a consistent, learnable interface that efficiently controls for time delays, a factor that simulation environments aren’t hindered by.

“SenseAct is an important new step in machine learning research on robots, enabling consistent and reproducible results on physical robots for the first time. It will establish a standard that may greatly accelerate machine learning research on physical robots, pushing reinforcement learning to a new level of performance just as large standard data sets have for supervised learning,” said Richard S. Sutton, professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at University of Alberta.

SenseAct allows reinforcement learning agents written for OpenAI’s popular “gym” simulator to learn behaviors for robots, by insulating them from the complexity of real-time control of robotic components. SenseAct’s guiding principles of minimizing delays and maximizing timing consistency via proactive computation lead to responsive learned behavior and reliable learning via state-of-the-art algorithms.

“This initial release focuses on tasks that explore timing, control frequency, action representation, partial observation, and sparse reward. We intend to update SenseAct as we define new tasks to reflect challenges in developing efficient, general, intuitive behaviors for our current and future products,” says James Bergstra, Head of AI Research at Kindred.

SenseAct allows general reinforcement learning algorithms to learn diverse tasks on diverse robots, and is made freely available for anyone to explore and extend. For more information, visit www.kindred.ai/senseact

The Engineering People Show, Episode 25: Dr. Anurag Maunder

I know some engineers will be disappointed by that, but it’s easier for me to find a smart person than for me to find a hardworking person. If there is one message I can give to every young engineer is that don’t take working hard for granted.

Today on Engineering People

Dr. Anurag Maunder is an SVP of Engineering at Kindred AI, an artificial intelligence company that solves human problems with autonomous robots. He started his career with prestigious AT&T Bell Labs. He was the Founder and CTO of Kazeon Systems (later acquired by EMC) and the Founder CEO of dLoop (acquired by Box). In the last few years, he established the Advanced Development lab for EMC to focus on Machine learning for automating storage configurations, and also created Johnson Controls Innovation Garage, which introduced several new AI products in industrial IOT. His current areas of interest are AI, Robotics, Smart Buildings and IoT Security using Blockchains. He believes that AI and Robotics together will fundamentally transform the quality of life and disrupt every single industry.
(Listen to the original episode released on September 10, 2018)

Kindred announces integration partnership with Manhattan Associates' warehouse management system

 
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BUSINESS WIRE (MAY 2018) - Kindred, an AI and robotics company that builds human-like intelligence in machines, today announced that it has integrated its robotic solutions with Manhattan Associates’ market-leading Warehouse Management System (WMS). “Partnerships between robotics vendors and applications companies, like this one between Kindred and Manhattan, are incredibly valuable in delivering successful deployments of robots in non-traditional applications,” says John Santagate, research director for Service Robotics at IDC.

Kindred and Manhattan are demonstrating their combined solution this week at Manhattan’s Momentum Conference in Hollywood, Florida. In the demo, Manhattan’s WMS senses real-time system capacity and directs work to the Kindred SORT robot based on factors like item type, handling requirements, congestion, and machine learning-driven task duration estimates. Kindred will also be demoing how SORT uses a combination of reinforcement learning and supervised learning to quickly and accurately sort batches for order fulfillment and store replenishment.

“SORT arrives at our customers’ warehouses pre-trained and able to adapt easily to each customer’s unique inventory profile. It was an easy decision for us to integrate with Manhattan, a partner that is equally as dedicated to customizing the warehouse fulfillment process,” said Jim Liefer, CEO of Kindred. “We look forward to providing Manhattan customers with a seamless way to integrate robotic solutions in their warehouses.”

“We are pleased to partner with Kindred to illustrate our ability to orchestrate work across man and machine,” said Adam Kline, senior director of Product Management, Manhattan Associates. “The fact that we were able to get their robot to work with our WMS this quickly is testament to the power and flexibility of these two products.”

Integration with Kindred will be available immediately upon release of Manhattan Warehouse Management for Open Systems 2018.

Contacts:
Kindred
Michelle Kim, 844-344-2088 ext 712
michelle@kindred.ai