Deductive AI

We're extremely excited to welcome Arash Parsa to Deductive AI as our newest Founding Software Engineer! Arash joins us from Google Infra Spanner, where he was a tech lead on critical Spanner serving infrastructure projects and debugging rotations. Before Spanner, Arash spearheaded and led the development of the Cloud Firestore Key Visualizer from inception to launch for some of the largest GCP customers, in addition to other key contributions to GCP’s hotspot detection technologies. Today, the Key Visualizer for Firestore is an invaluable observability feature that is heavily relied upon by GCP customers for debugging and maintenance of their services! Before Google, Arash was a tech lead manager at Radius Intelligence working in the predictive data and ML space. He spent his undergraduate and graduate years at the University of California, Berkeley. At Deductive AI, we are solving some very hard/interesting problems in the area of code-aware observability, with a focus on building multi-agentic flows that can reason on extremely large amounts of data and code. If you are exceptional at what you do and are passionate about problems at the intersection of data and AI, please drop us a note!

Excited to share we are on a lookout for rockstar interns at Deductive AI. The role is based out of the London office in Camden. You will be working directly with me, while collaborating with the rest of the founding team in Mountain View. Apply here if you would like to work on Foundational AI, Agentic Systems and advanced data processing. https://lnkd.in/esHSd-xs

Happy Halloween and a Happy Diwali from team Deductive AI! Bonus points if you can spot our old and new logos. Aditya B., Karan Abrol, Krushnakant Bhattad, Madeline Cripps, Mustafa Mirza, Norm Zhou, Pratyush Verma, Rakesh Kothari, Shauna Blake, Yating Zhou

As the summer season wraps up, very excited to share that we're looking for a couple of exceptional fall interns at Deductive AI in Mountain View, CA. This is a paid, hands-on role where you'll work directly with me and our founding team on building the next generation of AI and data processing systems that can understand and reason about vast amounts of data and code. In the past, our interns have worked on some core problems around search and retrieval of structured and unstructured data, LLM evaluations, and reasoning over code & logs, making a direct impact on building Deductive from the ground up. Please apply here:

Excited to share that we're on the lookout for a talented front end / product engineer to join our team at Deductive AI! Previous experience with React is a plus, but not required. If you’re interested in working on a product at the intersection of Observability, AI, and data visualization, drop me a note to learn more.

Excited to share that we're looking for a few rockstar summer and fall interns at Deductive AI in Mountain View, CA. This is a very hands-on role where you'd be working directly with me and our amazing founding team on building the next generation of foundational AI and data processing systems that can reason on extremely large amounts of data and code.

A great article by Joanne Chen and Jaya Gupta from Foundation Capital discussing the service-as-software model (SaaS v2?) and highlighting the $4.6T TAM opportunity in this area: https://lnkd.in/gTWgU6mt. We’re very grateful for their nod to Deductive AI as one of the key future players in this area. It’s also a privilege to share this space with several amazing companies in the AI-powered code generation space that we deeply respect. With the rise in popularity and adoption of GitHub copilot, Codeium, Cognition, and other powerful tools, it would not be unreasonable to imagine that the amount of software products developed in the next decade will be orders of magnitude greater than those built in the previous one (in the famous words of Andrej Karpathy, “The hottest new programming language is English”). However, at the same time, if generative models are helping write large parts of this code, our software will become more opaque over time, making it increasingly difficult for engineers and on-calls to have complete context to root causes and mitigate outages. Looking forward to seeing how root-causing and the on-call models evolve as a result of this fundamental paradigm shift in the next few years, and humbled to play a small part in defining this future!

We're excited to welcome Aditya B. to Deductive AI as our Founding UX Designer! Aditya joins us from Splunk, where he led the product design for several key observability products at the company. Before Splunk, Aditya spearheaded the design of Spektra and Ultima at Diamanti, and played a pivotal role in designing Deserve's consumer credit card management platforms. He worked at VMware and T-Labs during his foundational years as a UX designer. At Deductive, we are building the next generation of foundational data processing systems that can reason on (and not just query) extremely large amounts of data. If you are exceptional at what you do and are passionate about problems at the intersection of data and AI, please drop us a note!

A good article from Unusual Ventures on future trends in observability: https://lnkd.in/dCXEn-wZ. We're very grateful for their nod to Deductive AI as one of the innovators in the AI-powered reasoning space! Thinking along these lines, as we look at the evolution of databases and large-scale observability systems over the past decade, our industry has achieved remarkable progress in querying large datasets characterized by high dimensionality and cardinality. However, despite these advancements, the process of root cause analysis remains significantly hindered by the cost of storing this data and the domain knowledge required of engineers and on-calls to know what needs to be queried. It's fascinating to see how organizations are paying millions of dollars to collect, store, and process their metrics, logs, events, traces, and it still takes hours, if not days, for people to debug any non-trivial issues in production. While we're still in stealth, it has been a really fascinating and humbling journey over the last few months to build (and experience) firsthand the power of AI and approximations in fundamentally disrupting some of these age-old inefficiencies by enabling systems that can reason on (and not just query) large amounts of data. Looking forward to sharing more about what we're building in the coming months!

We're delighted to welcome Madeline Cripps to Deductive AI as our newest Founding Engineer! Maddie joins us from Meta, where she spent the last 6 years building the next generation of Meta's observability stack, with numerous key contributions spanning across Scuba, ODS, and Tracery. At Deductive, we are solving some very hard/interesting problems at the intersection of AI, approximations, and data analytics, with a focus on enabling real-time reasoning on massive data streams. If you are exceptional at what you do and are passionate about problems at the intersection of data and AI, please drop us a note!