Leksei

Data Pipelines written by AI.
Verifiable. Every time.

Don't let AI near your SQL.
In high-stakes environments, a single hallucination is a non-starter. Leksei generates strictly typed code that enforces semantics, privacy, and lineage by design—giving you the speed of AI with the guarantees required for your most sensitive data.

Deploy to your own Data Warehouse Type-Safe
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You Architect. Leksei Codes.

The agility and raw power of AI, grounded by rigorous guardrails.
Operate at the level of logic, not syntax.

  1. 1.Define the Goal

    Describe the outcome in plain English using your business terms.

    "Calculate MAU by region…"

  2. 2.Verify the Logic

    Leksei maps your request to clean, readable Xander code and transparent workflows.
    Everything in plain sight.

    [ Code ] + [ Graph ]

  3. 3.Secure Execution

    Your logic runs natively inside your warehouse.
    Data never leaves your perimeter.

    • Snowflake
    • Databricks
    • BigQuery
    • Redshift
    • Synapse
    • ClickHouse
    • DuckDB
    • and more…

SQL was not built for AI.
Xander was.

Standard SQL is too permissive for generative models, leading to silent errors. Xander is purpose-built to constrain the LLM—forcing it to produce strictly typed, immutable business logic.

Explicit by Design

Xander’s syntax provides the rich context AI needs to be accurate, and the clarity humans need to verify it. Since the AI handles the authorship, you get rigorous, self-documenting code without the manual overhead. It is the difference between a "probability" and a guarantee.


	
	

8@each lead @in leads



9  //? Semantic Definition (Auto-updated)



10  @where lead[region] @in USMCA



11  //? Verified Type Safety



12  @where lead[score] > 85



13  //? Native Object Validation



14  @where lead[@Email] @is @Email {



15  lead



16}




SELECT * FROM leads
-- Implicit Schema Access (Are these Strings? Ints? Do they exist?)
WHERE
    -- Manual list (Who updates this when Costa Rica joins?)
    region IN ('US', 'CA', 'MX') AND
    -- Unsafe Cast (Pray score is an integer)
    score > 85 AND
    -- Maintenance Nightmare
    REGEXP_LIKE(
	        email,
		    '^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}$'
		);
1974
  • Implicit scope ("Magic" columns),
  • hardcoded lists,
  • and fragile string matching.
 2026
  • Explicit member access,
  • semantic definitions,
  • and native types.

Zero. Data. Movement.

Your data has gravity. We respect it.
We transmit the logic, not the mass. Transformations compile to native code and execute entirely within your walls, leveraging the compute you already pay for.

managed
Leksei Cloud

The fastest way to start. Fully managed control plane hosted by us.

  • Zero configuration
  • Community Semantic Registry
  • US, EU & APAC Regions
isolated
Dedicated

Infrastructure managed by us, but isolated for you for a higher level of service.

  • SSO SAML available
  • Private Networking
  • 99.9% Uptime SLA
  • Custom Data Residency
on-prem
Self-Hosted

Run a Leksei platform node in your own servers. Total air-gap.

  • Best for teams with heightened security requirements
  • Telemetry Sovereignty. Strictly opt-in and air-gap capable
  • BYOK Encryption
  • Kubernetes Native
*In all deployment models, your data remains in your warehouse. Only the Control Plane is hosted.

Xander is on your side.

Xander handles the plumbing—privacy, versioning, and semantics—natively, so you can focus on the outcome. It is modern ergonomics for data logic: effortless to audit and a joy to write.

Native Semantics

Embed your business ontology directly in the code. No need to maintain parallel YAML files or external semantic layers. The engine understands the data because the taxonomy is native.

@let (
  [ common: [ ID ], logistics: [ supplier ] ]: @org("Leksei")
  [ authorized_substances ]: @org("ECHA")
  [ logistics: [ verified_vendors ] ]: @org("CyberdyneSystems")
  [ qc: [ purity ] ]: @org("WeylandYutani")
)

@each compound @in compounds
  @where
    //? The Law: EU Chemical Safety (Government)
    compound[ID] @in authorized_substances[@v"1.0.2122"] @and
    //? The network: Leveraging a partner's vetted supply chain (B2B)
    compound[supplier][ID] @in verified_vendors @and
    //? The Policy: Internal Aerospace Specs (Customer)
    compound[purity] >= purity.aerospace_grade {
  compound
}

Privacy as a Primitive

Redaction isn’t a bolted-on setting; it’s a data type. Mark fields as Secret and the compiler mathematically guarantees that data cannot leak to unauthorized outputs.

safe_to_log:
  "Dr. {
    @Secret(doc[family_name]).allow([medical_director])
  } prescribed {
    @Secret(drug[active_compound]).allow([pharmacist])
  } to patient {
    @Secret(patient[mrn])
  }."

Versioning in Syntax

Stop wondering why the numbers changed. Versioning is built into the language syntax. You can reference specific versions of a definition within the same expression.

@let delta: revenue[@v"2.0.10"](data) - revenue[@v"1.2.1"](data)

Hallucinations don’t compile

Xander is strictly typed with full type inference. If the LLM invents a column or mocks up a relationship that doesn’t exist, the compiler blocks it instantly.

error: Property "merchID" doesn’t exist on transaction
Did you mean "merchant_id"?

Be the Architect.
Let AI be the Author.

Stop debugging syntax and start shipping value. Equip your team with the only platform that turns natural language into rigorous, verifiable business logic.