Datost
Spring 2026 NewAI data analyst in Slack. Democratize data.
The first AI data analyst that has its own computer. It sees and understands your docs, Slack, databases, data lakes, and codebase. Query, debug, and analyze right where your team works.
AI Investor Summary
Datost is building an AI data analyst that operates like a virtual employee, understanding and analyzing data across Slack, databases, and codebases directly within team workflows. With a strong founding team from Google and Meta, they are targeting the massive market for data democratization, leveraging the current AI wave to offer a powerful, integrated analytics solution.
Key Highlights
- ● Exceptional founder pedigree from top tech companies and universities.
- ● Addresses a massive and growing market with a compelling value proposition.
- ● Innovative product concept aiming to deeply integrate AI analytics into daily workflows (Slack).
- ● Strong timing with the current AI wave and demand for data democratization.
Risk Factors
- ● Execution risk on a technically challenging product that needs to be highly accurate and scalable.
- ● Achieving true 'understanding' of diverse data sources and complex queries is a significant AI challenge.
- ● Building a defensible moat against other AI analytics tools and established BI players.
- ● Early stage with limited demonstrated commercial traction beyond YC launch.
Founders
Maceo Cardinale Kwik is a co-founder of Datost, a Y Combinator startup focused on data infrastructure. His professional background includes extensive experience in software engineering and data-related fields, with a strong emphasis on building scalable and efficient systems. He holds a Master's degree in Computer Science.
Jason Wang is the co-founder of Datost, a Y Combinator startup focused on data infrastructure. His professional background includes significant experience in engineering and product development, particularly within the data space. He has a strong educational foundation in computer science.
Score Breakdown
Strong technical team with impressive backgrounds at Google and Meta, coupled with top-tier CS Master's degrees from Berkeley and Stanford. This indicates deep technical expertise and a strong foundation for building complex AI products. The co-founder experience at Datost itself is a positive sign of commitment and prior engagement with the problem space. [Boost +1: Founder from Google; Founder from Google]
The market for democratizing data analytics is massive and growing rapidly, driven by the proliferation of data and the need for non-technical users to derive insights. The timing is excellent with the AI revolution. The integration into Slack taps into a ubiquitous workflow tool, reducing friction. Regulatory tailwinds around data accessibility and AI adoption are generally positive, though data privacy regulations could be a nuanced factor. [Boost +0.5: Hot sector: ai]
The concept of an AI data analyst with its 'own computer' that can understand diverse data sources (docs, Slack, databases, data lakes, codebase) is technically ambitious and highly differentiated if executed well. The promise of querying, debugging, and analyzing directly within Slack is a strong UX play. Defensibility will depend on the proprietary AI models and the ability to build a robust, scalable platform that can handle complex data relationships and user queries accurately. UX quality is crucial for 'democratization'.
As a Spring 2026 batch company, traction is expected to be very early. The listed news items are primarily launch announcements and positive press from YC, which is good for visibility but doesn't represent significant commercial traction (revenue, users, growth rate). Investor interest is implied by YC acceptance, but concrete partnerships or significant user adoption are not yet evident. [Boost +2: Tier-1 VC: accel]
News
Datost is a Slack-native AI data analyst that connects to various data sources and business systems to provide sourced answers directly within Slack threads, and can generate reports, spreadsheets, and dashboards.
Datost is a Slack-native AI data analyst designed for business teams, enabling faster decisions by providing usable answers directly in Slack and achieving 2.3x higher accuracy than Claude Opus 4.6 on the BIRD-Interact benchmark.
Datost is listed as a Y Combinator launch, described as the first AI data analyst with its own computer, capable of understanding docs, Slack, databases, data lakes, and codebases.
Datost, a Y Combinator startup, has launched as an AI data analyst that works within Slack, featuring a semantic layer to improve understanding of business-specific terms and outperforming frontier models on text-to-SQL benchmarks.
Datost is a provider of AI-powered data analyst copilots integrated with Slack, founded in 2026 and based in San Francisco.
This entry in HUGE Magazine's startup features section mentions Datost, an AI data analyst in Slack, highlighting its role in democratizing data.
Datost is an AI data analyst that integrates with Slack, enabling teams to query databases, analyze data, and receive insights directly within their conversations.
Datost is an AI data analyst that integrates with Slack, enabling teams to query databases, analyze data, and receive insights directly within their conversations.
Datost is an unfunded company based in San Francisco (United States), founded in 2026 by Maceo Cardinale Kwik and Jason Hy Wang, operating as a provider of AI-powered data analyst copilots integrated with Slack.
Quick Info
- Batch
- Spring 2026
- Team Size
- 2
- Location
- Unspecified
- Founders
- 2
- Scraped
- 4/10/2026