Datost is an AI data analyst with its own computer environment that can see and understand a company’s documents, Slack conversations, databases, and codebases, enabling teams to query, debug, and analyze data directly within the tools where that work already happens. Traditional data analysis often requires routing requests through a data team or learning specialized query tools, creating friction and delay for the people who need answers; Datost addresses this by giving an AI agent direct visual and contextual access to the full range of a company’s data sources, allowing it to answer questions and perform analysis across systems without requiring users to manually extract or prepare data first. The platform targets SMB and mid-market companies and differentiates through the breadth of data sources it can directly access and reason over — spanning documents, communication, databases, and code — within a single agent.
Datost
AI data analyst that sees your docs, Slack, databases, and code.
Compliance
SOC 2
Key Features
- Multi-source data understanding: Directly accesses and understands documents, Slack messages, databases, and codebases, giving it the context needed to answer questions that span multiple systems.
- Dedicated agent computer: Operates with its own computing environment, enabling it to run queries, execute code, and process data directly rather than being limited to passive retrieval.
- In-context querying: Allows teams to ask questions and get analysis directly within the tools they already use, reducing the friction of routing requests through a separate data team or BI tool.
- Codebase debugging support: Understands codebases well enough to assist with debugging tasks, extending its utility beyond pure data analysis into technical troubleshooting.
- Multi-model architecture: Uses multiple underlying LLM providers to power its understanding and analysis across the diverse data sources it connects to.
Use Cases
- For teams without dedicated data analyst support: A small product or operations team without access to a dedicated data analyst uses Datost to query databases and analyze data directly, getting answers without waiting on a centralized data team’s bandwidth.
- For engineering teams debugging issues across systems: A development team investigating an issue that spans application logs, Slack discussion, and database state uses Datost to pull context from all relevant sources and assist with root cause analysis.
Pricing MODELS
Enterprise, Saas subscription
Pricing Summary
Datost uses a SaaS subscription model with custom enterprise pricing for larger organizations. Specific pricing tiers are not publicly listed — organizations contact the company for a quote.
Company Size Fit
Mid-market SMB
Technical Snapshot
API Available
Yes
LLM Provider
Multi-model
Open Source
No
Deployment Options
Cloud Saas