With industry eyes focused on the potential of agentic AI, one startup wants to transform support and operations teams with agents and reduce the pressure placed on human workers.
Applied Labs, founded by former Scale AI leaders Michael Woo and Soham Waychal, has raised $4.2 million as part of a seed funding round led by Abstract.
The investment round saw participation from Point72 Ventures, Outlander, and Tetra, as well as pledges from angel investors including ex-Twitter exec Ali Rowghani.
Founded in January 2024, Applied Labs wants to embed AI agents within enterprise support and operations teams. The firm’s flagship solution offers users an end-to-end AI customer support agent trained on the businesses’ unique individual knowledge base.
The inspiration behind the startup comes from Woo and Waychal’s firsthand experience developing AI applications at Scale AI. The duo noted the cumbersome, repetitive nature of support interactions and ops workflows, and saw an opportunity to streamline the process.
"For companies, there's an explosion of C-Suite and boardroom interest into the question, what is our AI strategy?" said Michael Woo, CEO of Applied Labs.
"The bottleneck isn't the model anymore - LLM quality, speed and cost have reached an inflection point where almost every business can save time, cost and improve the quality of their support and ops.
“The challenge is in the data, tools and platform for teams to easily set up and perfect AI agents on their business-critical workflows. We’re obsessed with making our AI agents the best where if you’re not using them, you’re falling behind."
The Applied Labs investment comes at a critical time in the evolution of AI agents, with a host of major industry players such as Salesforce, Google, and Microsoft having unveiled their own agentic AI services.
At Applied Labs, the founder team believes they’re more than capable of building high quality, reliable, and easily-deployable agents that can compete with industry heavyweights.
The startup’s agentic AI solution focuses on three specific – and critical – areas that will deliver the best results for users. This includes:
- Omnichannel interactions spanning chat, email, and phone to handle request volumes
- AI agent orchestration for handling Q&A and AI workflows
- Evaluation tools for testing, auditing, and monitoring AI outputs
Notably, this approach also includes in-built human-in-the-loop options, helping users find the right balance between efficiency and human touch for complex or emotionally-charged situations.
“AI allows you to scale up your best human judgement on an infinite volume of tasks but human judgment is still necessary to get the best quality results and handle edge cases.“ Woo said.
This human-in-the-loop aspect is a key differentiator, according to Woo. A single misstep or botched customer inquiry can seriously erode trust and create more problems down the line.
“At Scale when we first did AI labeling or if you think about self-driving cars or even these AI sales agents, if you scale up a poorly thought out AI response or workflow on high volume, it’s deeply damaging.” Woo said.
Woo noted that the firm’s in-built guardrails and monitoring systems ensure rigorous testing of the AI and human auditing before deployment.
This latest investment brings the total raised by Applied Labs to $5.2 million and will be used to double the firm’s headcount in the coming months. The startup revealed plans to accelerate engineer role hiring to advance its product roadmap.
“Few founders truly grasp the operational intricacies of deploying AI in mission-critical workflows,” said Ramtin Naimi, founder & general partner at Abstract.
“Michael’s experience managing Scale AI’s core data product brings a rare fusion of technical acumen and practical experience — exactly what’s needed to make AI both dependable and transformative. Applied Labs’ commitment to pairing trust with capability, underpinned by their human-in-the-loop approach, is precisely what enterprises need to confidently embrace AI-powered customer support.”
