Most CRMs are full of duplicates, messy hierarchies, and inaccurate firmographics, leaving RevOps teams fighting data hygiene issues instead of driving revenue.
Kernel tackles data inaccuracy at the source with an agentic entity database. It links accounts to real-world organizations, and its agents crawl and reason over CRM context and public sources to provide accurate data tailored to how your company sells.
Kernel’s data management platform performs expert-level data corrections safely at scale, applying the same decisions a RevOps professional would make for each account across your entire CRM.
Unlike traditional data providers, Kernel continuously maintains and updates data so it aligns with your go-to-market strategy, giving your team an accurate foundation to plan territories, identify whitespace, and increase rep productivity.
Teams at Gong, Navan, and Mistral AI trust Kernel to fix their foundational account data.
Rating Reviews
Rating is calculated based on
4
reviews and is evolving.
Pros: The intellectual caliber of colleagues is exceptionally high, making collaboration incredibly rewarding. There's a genuine opportunity to work on truly novel AI research problems, especially within the computational neuroscience space. The drive and vision behind the company are infectious, and you feel like you're part of something significant. Leadership is generally accessible and passionate about the mission.
Cons: As with many fast-paced tech startups, the workload can be intense, sometimes blurring the lines between work and personal time, though flexibility is usually offered. Some internal processes, particularly around approvals for research tools or project scope, could be streamlined to improve efficiency. Career progression paths, while present, might not always be clearly defined for specialized technical roles.
Advice to Management: Consider clearer frameworks for career pathing within specialized technical domains and look for ways to further streamline cross-functional approval processes during intense project phases.
Show more
Pros: Kernel offers a dynamic and intellectually stimulating environment. The teams are composed of smart, driven individuals passionate about AI and machine learning. I've appreciated the opportunities for hands-on learning and contributing to cutting-edge technology. The hybrid work setup in London is well-managed, and the company culture encourages open communication and idea sharing.
Cons: While the growth is exciting, sometimes the rapid pace can lead to less structured processes or occasional scope creep on projects. Ensuring clear documentation and more defined long-term roadmaps would further enhance efficiency and predictability for the engineering team. Some benefits could be more competitive compared to larger tech firms.
Advice to Management: Focus on formalizing some processes to match the company's ambitious growth, and consider enhancing the benefits package to remain competitive in the London tech talent market.
Show more
Pros: The cutting-edge research and development opportunities are a major draw. I've learned a lot and feel like I'm contributing to something significant. The collaborative environment among the R&D teams is excellent, and people are passionate about the mission. The company offers competitive pay and benefits for the biotech sector.
Cons: While career growth is good, advancement paths can sometimes feel a bit unclear or dependent on specific project needs. The pace can be intense, leading to occasional long hours, particularly around project deadlines. Management's strategic vision is strong, but communication of day-to-day priorities could sometimes be more streamlined.
Advice to Management: Consider formalizing career progression frameworks and ensuring clearer communication channels for project priorities to help employees navigate growth opportunities more effectively.
Show more
What's the dress code like at Kernel, especially for roles in the tech industry in San Francisco?
At Kernel, the dress code is pretty relaxed and focuses on comfort, which is great for our fast-paced tech environment in San Francisco. You'll see most people in casual wear like jeans and t-shirts, so climate-appropriate clothing is key.
What's the interview process like for a software engineer at Kernel, a Series B AI company in San Francisco?
My interview process at Kernel involved a technical screen, followed by a few rounds of virtual interviews covering system design and behavioral questions, typical for a Series B AI company in San Francisco.
What is the hiring process like at Kernel for a software engineer role in San Francisco?
My hiring process at Kernel for a software engineer position in San Francisco involved a technical screen, followed by a couple of virtual interviews focusing on system design and coding. It was a pretty standard but thorough process for a tech company of their size.
What's the typical salary range for a software engineer at Kernel, and do they offer good benefits?
For a mid-level software engineer role at Kernel, I've seen offers generally ranging from $120k to $160k base salary, with additional stock options. The benefits package is quite comprehensive, including good health insurance and generous PTO, which really helped ease the transition when I joined the team.
US
