lanikaia

01 / Product Detail

Turn each ask into Data MCP, Data Agent, and Data App artifacts.

Lanikaia is the execution layer above your data platform. It takes an executive or operational ask and keeps the data, definitions, generated code, approval state, and output together as one reusable unit of work. A CDO or Head of Data can evaluate what artifact is produced, who can inspect it, and how far it can be reused.

02 / Artifacts

Lanikaia produces three concrete artifacts.

  1. 01

    Data MCP

    A governed interface for data use

    Datasets, functions, metrics, policies, and lineage are published as MCP tools. Agents and internal tools can call only the data and definitions they are allowed to use.

    Evaluation lens: can existing metrics, dbt assets, and policies be called safely as MCP tools?

  2. 02

    Data Agent

    An agent that advances an ask into executable work

    A natural-language ask becomes a work unit with referenced data, generated code, intermediate tables, review context, and approval state. It is not a chat transcript. It is reproducible analysis history.

    Evaluation lens: can the same ask be rerun by another team, another period, or another data snapshot?

  3. 03

    Data App

    A business surface for verified findings

    Verified results are published to workflows, approvals, operational views, APIs, MCP, BI, or Excel output. Analysis does not end as a report. It enters operating cadence.

    Evaluation lens: where does the output connect to board review, weekly review, or daily operation?

03 / Product Flow

One ask moves through five states.

  1. 01

    Ask

    A user asks in business language. Example: why did churn rise among our key accounts?

  2. 02

    Context

    Lanikaia gathers metrics, policies, catalog grants, and related history, then fixes the definitions and readable scope before execution.

  3. 03

    Execute

    The agent generates SQL, Python, or workflow logic and runs it against Iceberg snapshots and semantic assets.

  4. 04

    Review

    Analysts, domain experts, and data owners inspect the answer, generated code, source references, and approval state in one place.

  5. 05

    Promote

    Only valuable work is promoted into a Data MCP, Data Agent, or Data App for reuse.

04 / Evaluators

Each reader should know what to inspect.

05 / Next Step

Evaluate the product with one real workload.

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