Maxa
Founded 2019 · 83 employees on LinkedIn · 6 known investors
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Maxa is an agentic platform that uses AI agents to build and maintain production-grade dbt data pipelines for finance and operations teams, unifying enterprise systems like SAP, Oracle, Salesforce, and Workday into a single data model. It generates auditable, self-verifying star schemas and marts with built-in tests and lineage that customers own in their own repositories and warehouses.
Also known as Maxa · Maxa.ai
Founders & leadership
Maxa was founded in 2019 by Alexis C. Steinman.

Investors · 6
Funding
SEC filings, press & company announcements$21M disclosed across 1 of 2 rounds · 2022–2024
Source: company announcements and press reports — follow each round's link for the claim.
Company profile
researched Aug 2026Maxa provides an agentic platform that generates and maintains multi-system data pipelines for finance and operations use cases. Its workflow has three stages: agents ingest unstructured business context — meeting transcripts, dashboard screenshots, spreadsheets, PDFs, sample data, ERP configs, DDL/schemas, existing dbt projects and BI models — and convert it into a unified specification, surfacing gaps for stakeholders to resolve before code is written. In the second stage, "Maxa Autopilot" writes dbt code while continuously validating it against the spec, historical reports and known business facts, with agents cross-checking each other's work until output figures match. In the third stage, the customer downloads the resulting dbt project and deploys it themselves.
The generated output is a standard dbt project containing star schemas and marts at arbitrary granularity, with schema, business-rule and reconciliation tests, documentation and end-to-end lineage traceable from source row to business requirement. Maxa states the code has no proprietary runtime dependency, lives in the customer's repository and continues to work if the customer changes warehouse, dbt tooling or vendor. The platform targets deployment on Databricks, Microsoft Fabric and Snowflake, and the resulting marts are intended to serve BI tools such as Tableau, Power BI, Looker and Sigma without an additional semantic modeling layer. Maxa also positions the models as a foundation for AI agents, embedding business context, lineage and metric definitions directly in the model rather than in separate semantic layers or ontologies.
On data handling, Maxa states it does not connect to or query customer production warehouses. Customers export schemas and a sample of rows — up to 10,000 per table — into a local database within their Maxa environment, where all agent work runs read-only against that copy.
Business model
Maxa sells access to an agentic pipeline-building platform; the site offers a free trial and a "talk to an expert" sales motion. The generated dbt code is owned and executed by the customer in their own repository and warehouse rather than on Maxa infrastructure.
▸Full profile — market position, technology, go-to-market
Market position
Maxa emphasizes readable, non-black-box standard dbt output that the customer owns and can modify or run without Maxa's infrastructure, correctness defined as matching known business figures rather than merely executing successfully, tests and lineage generated by default, and no requirement to build a separate semantic layer. It also emphasizes not touching production data, working only on an exported sample in a read-only local copy.", "go_to_market">
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Technology
AI agents that translate unstructured business inputs into specifications and then author production-grade dbt models, with agents cross-validating each other's output against the spec, historical reports and extracted concrete figures used as acceptance criteria. Generated projects include schema, business-rule and reconciliation tests, row-count parity, key integrity and source traceability checks, plus full lineage and documentation. A knowledge library encodes standard ERP module structures, while a discovery process searches customer data using concrete entities (customer IDs, invoice numbers) to locate tables in customized deployments, escalating cases where customizations change logic rather than table names.
Go-to-market
Enterprise finance and operations teams and the data teams supporting them, particularly organizations running ERP and enterprise systems such as SAP (FI/SD), Oracle Financials, Microsoft Dynamics 365 Finance, Salesforce and Workday.
Compiled by commissioned research from 1 cited public sources — announcements, filings, and press listed under research sources below.
Key figures
latest reportedCompany-reported or press-reported figures, each dated to when it was claimed — not independently audited.
In the news
▸Research sources · 1
primary sources listed
- Maxamaxa.ai · web
1 public sources were cited for this profile; the first-party ones are listed here.
Frequently asked questions
- What does Maxa do?
- Maxa is an agentic platform whose AI agents build production-grade dbt data pipelines for finance and operations teams.
- Who founded Maxa?
- Maxa was founded by Alexis C. Steinman in 2019.
- Who are Maxa's investors?
- Maxa's investors include Framework Venture Partners, Graphite Ventures, NAventures, AQC Capital, BDC Capital Corporation, York IE.
- How much funding has Maxa raised?
- Maxa has disclosed $21M raised across 1 of its 2 known rounds.

