Alkera Ai website screenshot

Alkera Ai

Alkera is an AI data-engineering agent that works across your data stack from the command line and inside your editor to build, migrate, optimize, and debug data pipelines. It ships as a CLI and an IDE extension (VS Code and Open VSX forks such as Cursor and Windsurf), and pairs a cross-platform column-level lineage engine with a living knowledge base so the agent understands what your data means and what your team already decided about it. Alkera connects natively to 14+ platforms including Snowflake, Databricks, BigQuery, dbt, and Airflow, builds new pipelines end to end (sources, models, tests, orchestration), migrates legacy systems while verifying functional equivalence, removes dead pipelines, refactors slow models, and performs root-cause analysis with blast-radius awareness. It ranked first on DataAgentBench (83.28% Pass@1). Enterprise deployments add SSO/SAML, SCIM & IAM, audit logs, pooled usage, VPC and on-prem deployment, zero data retention by default, data residency controls, and SLAs.

Alkera Ai is profiled on the APIs.io network. Tagged areas include Company, Data Engineering, AI Agents, Data Pipelines, and Data Lineage.

Alkera Ai’s developer surface includes documentation, getting-started guide, pricing, signup flow, changelog, CLI, and 11 more developer resources.

24.7/100 emerging ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5
0 APIs
CompanyData EngineeringAI AgentsData PipelinesData LineageDeveloper ToolsCLIIDE ExtensionData Stack

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 24.7/100 · emerging
Contract Quality 0.0 / 25
Developer Ergonomics 7.0 / 20
Commercial Clarity 8.9 / 20
Operational Transparency 2.1 / 13
Governance 0.0 / 12
Discoverability 6.8 / 10
Agent readiness — 0/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 0 / 12
Machine-Readable Auth 0 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/alkera-ai: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Alkera Ai Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 4

Portal, sign-up, and the first successful call

Documentation 1

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Build 2

SDKs, sample code, and the tooling you integrate with

Access & Security 1

Authentication, authorization, and security posture

Operate 2

Status, limits, changes, and where to get help

Commercial 3

Pricing, plans, and the legal terms of use

Company 1

The organization behind the API

Other 1

Properties that don't map to a standard resource type

Source (apis.yml)

apis.yml Raw ↑
aid: alkera-ai
name: Alkera Ai
description: Alkera is an AI data-engineering agent that works across your data stack from the command line and inside your
  editor to build, migrate, optimize, and debug data pipelines. It ships as a CLI and an IDE extension (VS Code and Open VSX
  forks such as Cursor and Windsurf), and pairs a cross-platform column-level lineage engine with a living knowledge base
  so the agent understands what your data means and what your team already decided about it. Alkera connects natively to 14+
  platforms including Snowflake, Databricks, BigQuery, dbt, and Airflow, builds new pipelines end to end (sources, models,
  tests, orchestration), migrates legacy systems while verifying functional equivalence, removes dead pipelines, refactors
  slow models, and performs root-cause analysis with blast-radius awareness. It ranked first on DataAgentBench (83.28% Pass@1).
  Enterprise deployments add SSO/SAML, SCIM & IAM, audit logs, pooled usage, VPC and on-prem deployment, zero data retention
  by default, data residency controls, and SLAs.
url: https://raw.githubusercontent.com/api-evangelist/alkera-ai/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- y-combinator
x-tier: stub
x-tier-reason: portfolio-lead
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://alkera.ai/og-image.png
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-17'
tags:
- Company
- Data Engineering
- AI Agents
- Data Pipelines
- Data Lineage
- Developer Tools
- CLI
- IDE Extension
- Data Stack
apis: []
common:
- type: DomainSecurity
  url: security/alkera-ai-domain-security.yml
- type: Website
  url: https://alkera.ai
- type: DeveloperPortal
  url: https://docs.alkera.ai
- type: Documentation
  url: https://docs.alkera.ai
- type: GettingStarted
  url: https://docs.alkera.ai/quickstart
- type: Installation
  url: https://docs.alkera.ai/installation
- type: Pricing
  url: https://alkera.ai/pricing
- type: SignUp
  url: https://app.alkera.ai
- type: Login
  url: https://app.alkera.ai
- type: TermsOfService
  url: https://alkera.ai/tos
- type: PrivacyPolicy
  url: https://alkera.ai/privacy-policy
- type: ChangeLog
  url: https://docs.alkera.ai/changelog
- type: ChangeLog
  name: Alkera changelog artifact
  url: changelog/alkera-ai-changelog.yml
- type: LLMsTxt
  url: llms/alkera-ai-llms.txt
- type: Packages
  url: packages/alkera-ai-packages.yml
- type: CLI
  url: cli/alkera-ai-cli.yml
- type: Lifecycle
  url: lifecycle/alkera-ai-lifecycle.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence