AGENTIC DATA ENGINEERING

Data Request To Resolution:

Hours, Not Months

99% faster across the full lifecycle — discovery, build, validation, and testing. Tabsdata is the first data engineering platform where the agent and the infrastructure are one system.

Prove it on one workload

Why Bolted-On Agents Fail

Every data platform is bolting on agents — and an agent stitched across disconnected tools operates blind: it can't see the lineage, semantics, or dependencies that live in the systems around it, so it breaks what it can't see. Tabsdata was built the other way around: one system where the agent sees every table, every version, every dependency, and every definition — kept current by a living semantic catalog that classifies data the moment it connects. That's what makes it fast and safe.

Bolted-On Agents
What the agent sees
Every table, version, dependency, and definition inone system
One tool at a time; blind at every platform boundary
Lineage
Native lineage — produced by execution, available to the agent at every step
Reconstructed as best effort after the fact, if at all
Validation
Incremental validation before anything propagates
Changes land, then you find out
Blast radius of a mistake
Bounded — every change is a new version, never a mutation
Unbounded — downstream breakage discovered next morning
Who approves
A human, every time
Often nobody

Fast, Safe, and Easy To Adopt

Speed You Can Audit

The 99% isn't one magic step. It's measurable compression at every stage of the request lifecycle — discovery, duplication checks, build, and testing — and you can inspect each one.

Safe by Construction, Not by Supervision

Versioned immutable tables, lineage produced by execution itself, and human approval on every change. The agent can't break what it can't see — because it sees everything.

Lands Beside Your Stack, Not on Top of It

Start with a net-new workload. Databricks, Snowflake, BigQuery, AWS — everything you run today keeps doing its job, and Tabsdata delivers governed, versioned tables straight into it. No migration, no rip-and-replace, no bet-the-company decision on day one.

The Request Lifecycle,  Compressed

Stage 1 — Discovery

The living semantic catalog classifies every source and destination the moment it's connected. When a request arrives, the agent already knows what data exists, what it means, and where it lives. Weeks of hunting becomes minutes.

Stage 2 — Duplication Check

Before building anything, the agent checks whether the answer — or most of it — already exists. Redundant pipelines are the silent tax on every data team; here they never get built.

Stage 3 — Incremental validation

The agent assembles the dataflow step by step, materializing checkpoints along the way so the requester validates intermediate results as they emerge — not after a month of waiting for a big reveal.

Stage 4 — Regression & Acceptance

Every change is tested against prior versions before it lands. Because every table is versioned and every execution is recorded, regression testing is native, not a bolted-on QA phase.

Built For The Team That Owns The Backlog

For Data Leaders
(CDO, VP Data & Analytics)

Your backlog is the most visible number in the company, and every request in it ages in weeks. Tabsdata changes the unit of measure — requests resolved in hours, with full lineage and human approval on every change, so speed never comes at the cost of a governance incident.

For Platform & Data Engineers
‍

Tabsdata doesn't automate your judgment — it amplifies it. The agent does the discovery, the duplication checks, and the boilerplate; you make the calls that matter and approve what ships. Less time in the ticket queue, more time on the work that needs an engineer.

Your Data, Your Network

Tabsdata deploys in your cloud, hybrid, or fully on-premises. Role-based access control, full audit logging, and versioned history of every change — the governance story isn't a feature tier, it's the architecture.

Deploy Tabsdata In Public Or Private Clouds

Tabsdata runs on Kubernetes and may be deployed on self-managed Kubernetes clusters or public cloud Kubernetes services including server less infrastructure.

Deploy Tabsdata On Premises

Tabsdata can be deployed on bare metal infrastructure and can run on development laptops and workstations.

Don't Take The Number On Faith — Test it

Pick one workload — net-new or fragile. We'll prove the compression in 30 days, measured against your current time-to-resolution.

Prove it on one workload

Frequently Asked Questions

  • What is Tabsdata?

    Tabsdata is an agentic data engineering platform. It resolves data requests — from discovery through build, validation, and testing — in hours instead of months, because the AI agent and the data infrastructure are built as one system. The agent has full visibility into every table, version, dependency, and definition, and a human approves every change.

  • How does Tabsdata resolve data requests 99% faster?

    The compression happens at every stage of the lifecycle. Discovery is near-instant because a living semantic catalog classifies data as connections are created. Duplication is caught before anything is built. Builds are validated incrementally with materialized checkpoints instead of a final big reveal. And regression testing is native, because every table version and execution is recorded. No single stage is magic; the 99% is the product of compressing all of them.

  • Is it safe to let an agent touch my data infrastructure?

    In Tabsdata, the agent never mutates data — every change creates a new immutable version, so nothing is destroyed and everything can be rolled back. Lineage is produced by execution itself, so the agent always knows what depends on what. And no change lands without human approval. Safety is a property of the architecture, not a supervision policy.

  • What is the living semantic catalog?

    The living semantic catalog is what gives the agent its context. When a source or destination is connected, Tabsdata automatically classifies its metadata using LLM-driven analysis and adds it to the catalog — and the catalog keeps updating as your data landscape changes. No manual curation, no dedicated ontology team. It's what lets the agent answer "what data do we have and what does it mean" in seconds.

  • How is Tabsdata priced?

    Tabsdata is free for self-supported deployments — the full platform, including the agent, the living semantic catalog, and lineage. Paid contracts add 24/7 support and full indemnification. Nothing about safety or context is an add-on SKU.

  • What is agentic data engineering?

    Agentic data engineering is the use of AI agents to carry out data engineering work end to end: finding the right data, checking for existing solutions, building dataflows, and testing changes. Most implementations bolt an agent onto a stack of disconnected tools. Tabsdata's approach is different: the agent operates inside a single system that natively tracks lineage, versions, and semantics, so it acts with full context.

  • How is this different from the agent features in data platforms such as BigQuery, Databricks, etc?

    Warehouse-native agents see their own platform and go blind at its boundary — and most real dataflows cross several tools. Tabsdata is not an agent added to a warehouse; it's a data engineering system designed so the agent sees the entire flow end to end, with lineage available at the moment it acts.

  • Does Tabsdata replace Databricks, Snowflake, or dbt?

    No. Your warehouse remains the center of gravity for storage, compute, and analytics — Tabsdata resolves the request lifecycle around it and delivers governed, versioned tables into it. Tabsdata lands beside your stack, starting with net-new workloads; existing pipelines and tools keep running untouched. Teams typically start with one new or fragile workload, prove the model, and expand from there.

  • What does a pilot look like?

    One workload, thirty days, one measurable claim: your current time-to-resolution versus Tabsdata's. You bring access, a champion, and a baseline; we deliver a working dataflow with full lineage and a measured result. Details at https://tabsdata.com/prove-it.

  • Where does Tabsdata deploy?

    Your cloud, hybrid, or fully on-premises. Data never leaves your network.

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