Our team at Edge Impulse has gained valuable insights from years of working with organizations at all maturity levels and experience with edge AI and ML. We have learned from talking to hundreds of engineers, product teams, and executive stakeholders that the friction of a poor workflow can affect a company's velocity, culture, and, ultimately, market viability.
Whether a company is diving into embedded AI or looking to improve existing infrastructure, it's logical to consider a DIY approach rather than a platform like ours. With that in mind, we have developed an ROI calculator to help decision-makers who need to know how to position their team for success. This tool empowers teams to conduct detailed financial comparisons, ensuring their ML investments are optimized for velocity, experimentation, and long-term success.
Access the ROI calculator online here.
Reasons for creating the ROI calculator
This online calculator resulted from many conversations between customer teams and our solution engineers. Too often, companies underestimate the burden and complexity of these projects, leading to budget overruns, missed deadlines, and long-term technical debt. It has become a valuable tool to demonstrate the pros and cons of building versus using a platform built, modified, and maintained by experts across the product lifecycle.
The ROI calculator our team uses internally is thorough but complex. We decided to create a public-facing web-based version that focuses on a few key elements, so teams could educate themselves about the implications of building, maintaining, and securing their own ML operations.
To address any concerns of bias, we vetted our results with experts and customers who have built in-house solutions to ensure we aren't tipping the scales. We have used this tool internally for some time, enhancing it with recommendations, scoring, and detailed pricing. We are committed to maintaining the best possible accuracy to empower organizations to make the best decisions for their future, even if it is not in our favor.
Understanding the ROI Calculator
We looked at the many projects we have been involved with and chose the most critical factors that influence the success of ML projects rather than requiring a massive amount of data. Here is what we ask and why:
How many engineers are on your team?
This slider helps estimate the labor costs associated with your project.
What is the mix of your team?
Your team's composition affects the project's overall efficiency and focus.
How new is your team to Edge ML?
This captures the potential learning curve and associated costs.
How complex is your data?
Data complexity here influences processing and model training expenses.
How complex are your sensors?
Complex sensor rigs require more upkeep, configuration, and processing power; these range from simple (Eg, a single temperature sensor) to complex (multiple sensor types running concurrently).
When would you like to ship your product?
Your timeline determines the urgency and resource allocation needed.
Once these inputs are set, the calculator breaks down the costs into three key categories:
- One-Time Costs: Initial investments in hardware, software licenses, setup, and development tools.
- Recurring Costs: Ongoing expenses such as salaries, cloud computing fees, and data storage are the fixed costs that "keep the lights on."
- Project Costs: Specific expenses related to data management, preprocessing, and other project-specific activities.
Using a few simple inputs, the calculator provides a clear view of the total cost of ownership for your ML project over the first three years and offers recommendations on whether to build in-house or opt for a solution like Edge Impulse. It then provides actionable insights and advice on how to proceed.
How Edge Impulse directly improves your ROI
Edge Impulse helps large organizations maximize ROI by streamlining ML development and reducing risks in three ways.
- Reducing Complexity: ML pipelines are more complex than most traditional software pipelines. Edge Impulse simplifies this by providing a platform that integrates the entire ML lifecycle, allowing teams to focus on innovation.
- Agile Readiness: ML projects need quick proof of concepts and fast iteration to validate ideas. Edge Impulse enhances agility with tools designed for rapid iteration, enabling quick pivots and strategy adjustments.
- Streamlining Costs: Training ML models is costly. Data acquisition, choosing the right target chipset, and scaling up infrastructure significantly affect budgets. Edge Impulse's tooling optimizes resources, reducing training time and GPU costs, and keeps projects lean.
Choosing between building in-house or using Edge Impulse is crucial. Our ROI calculator helps make this decision with confidence, reducing risk, accelerating deployments, and enhancing productivity for more successful and cost-effective ML initiatives. We hope for the opportunity to share our experience running the tools and services that power the world's most innovative products.
And once you get your results, we invite you to reach out to our team to go even deeper into what your use case will look like.