Datost

AI data analyst in Slack. Democratize data.

Spring 2026ActiveB2BAnalyticsB2BAnalyticsAI AssistantSan Francisco, CA, USA

Company

https://www.datost.com

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.

Note: This is a preliminary assessment based on limited publicly available information. We did not have access to LinkedIn profiles or live product screenshots for this analysis. We will update this entry with a more thorough review soon.

Verdict

Medium Signal

Market Opportunity

BI/analytics tooling is a real and large market ($10B+ TAM) with clear B2B ICP. The Slack-native angle is a legitimate distribution wedge since teams already live there. Enterprise features (SSO, SCIM, audit logs, RBAC) signal serious B2B intent. However, 'AI analyst in Slack' is crowded positioning and the differentiation from existing tools with Slack integrations isn't clearly articulated.

Medium Signal

Founder Signal

Maceo Cardinale Kwik: Virginia Tech CS Summa Cum Laude (4.0 GPA), SimonComputing full-time SWE for 1.5 years (built semantic search over 92k files, pgvector, Go backend, PostgreSQL 1.4M records), then Traba SWE where he explicitly built a data analyst agent generating research reports in Slack — the exact product Datost is building. Jason Wang: UofT CS/CE (AI minor), Confluent full-time SWE for 2+ years (Flink Control Plane — Apache Flink/Kafka data infrastructure, directly relevant), Red Hat intern (1 year), then Traba SWE. Both met and worked together at Traba before co-founding Datost — co-founders with prior working relationship is a green flag. Not elite schools, no prior exits, but genuine professional engineering experience with directly relevant domain skills.

Low Signal

Competition

The AI data analyst space is saturated: ThoughtSpot, Sigma, Mode, Metabase AI, and dozens of Slack-integrated analytics bots exist. More critically, major platforms like Databricks, Snowflake, and Google are building native AI query layers. No proprietary data moat or differentiated technical approach is articulated.

High Signal

Product

Product is live and substantially built. Website shows real Slack-native UI with working demos across multiple use cases (incident triage, renewal analysis, dashboard creation). Enterprise features visible: SSO + SCIM, Audit Logs, Role-Based Access, Human-in-the-Loop controls. Connection panel shows real admin UI managing databases (BigQuery, PostgreSQL, Databricks), log connections (Datadog, Sentry), GitHub repo indexing, Slack workspace sync, and MCP server integration (PostHog). Integrations include PostgreSQL, MySQL, BigQuery, Snowflake, Databricks, Firestore, Datadog, Sentry, PostHog, Slack, GitHub, Coda. Report generation and live dashboard creation from Slack messages is demonstrated with realistic output. This is a real, production-grade product — not vaporware.

OverallC Tier

Datost has a genuinely well-built product: Slack-native AI analyst with live database connections, dashboard generation, report creation, and real enterprise controls (SSO, SCIM, RBAC, audit logs). The integration surface is broad — BigQuery, Snowflake, Databricks, Datadog, GitHub, MCP servers. The founders have directly relevant experience: Maceo built a Slack data analyst agent at Traba before founding Datost, and Jason has 2+ years at Confluent on Flink/Kafka infrastructure. They met at Traba, which is a green flag. The problem is that despite a polished product, there are no named customers, no revenue, no testimonials, and no traction evidence visible. The competition is real: ThoughtSpot, Sigma, Metabase, and native AI layers from Databricks and Snowflake all converge on this space with existing customer bases. A strong product from a credible team, but C tier until customer proof exists.

Active Founders

Maceo Cardinale Kwik

Founder

Datost CEO & co-founder. Worked at Traba (backed by Founders Fund, Khosla, and GC) as a mid level software engineer. While I was there I built Datost after my 996 from 10pm-3am eventually getting 80% of the company using it.

Jason Wang

Founder

Datost(P26), co-founder. We're building the AI data analyst that lives in Slack. Previous software engineer @ Traba managing payment infrastructure with $200M+ annual volume University of Toronto Computer Engineering grad with minors in business and AI. While in school: completed 2 years of full-time engineering internships and ran a part-time real estate business, closing $10M in volume.

Datost

TierC Tier

BatchSpring 2026

Team Size2

StatusActive

LocationSan Francisco, CA, USA

Last Updated2 months ago

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