Alkera AI

Alkera AI is an agentic platform for data engineering, analytics and data science. It combines column-level lineage, a living knowledge base and connectors across warehouses, transformation/orchestration systems and BI tools so the agent can reason about downstream impact before changing data work.¹² Current first-party pages describe Snowflake, Databricks, BigQuery, Redshift, ClickHouse, DuckDB, PostgreSQL, MySQL/MariaDB, SQL Server, SQLite, Oracle, Trino, dbt and Airflow integrations, with analytics delivery into tools including Hex, Tableau, Power BI and Looker.¹²

The product spans pipeline creation and migration, root-cause analysis, automated insights, Jupyter-compatible notebooks and remote CPU/GPU/high-memory execution.² It is available through IDE, CLI and browser surfaces and can be delivered as managed SaaS or in customer VPC/on-prem environments.³⁴ AiToolMap did not perform hands-on testing of lineage accuracy, generated pipelines or remote-compute behavior.

Alkera is currently enterprise/demo-led. The public Terms reference product tiers and usage-based fees, but AiToolMap did not verify current public numeric plan prices during this audit.⁵ The catalog therefore retains enterprise contact-sales pricing rather than inventing a monthly figure.

This limits value-for-money certainty: teams can evaluate the product's technical fit from its public surface, but meaningful cost comparison requires a quote and an understanding of seat, model, compute and deployment charges. VPC/on-prem, enterprise identity controls and SLAs may also change commercial terms.

Alkera publishes a detailed security architecture. Its July 29, 2026 security page separates credentials and model access into distinct trust zones, says credentials are not directly exposed to the LLM, classifies tool calls as read, write, destroy or egress, and requires approval above read unless policy is explicitly configured otherwise.³ It also describes OS-level sandbox restrictions, SAML/OIDC, SCIM, MFA, encryption, signed images, SBOM generation and tamper-evident audit logs.³

The same page says SOC 2 Type II, ISO 27001, GDPR and HIPAA work is in process with external auditors; these should not be represented as completed certifications.³ The Privacy Policy, also updated July 29, 2026, contains broad personal-data provisions and states that conversation and personal data may be stored for up to six years unless an account is deleted, after which disposal is described as no longer than 60 days.⁶ Teams should reconcile that retention language with any zero-data-retention terms offered on eligible plans.¹

Alkera and Y Combinator state that Alkera ranked first on UC Berkeley's DataAgentBench with 83.28% Pass@1.¹⁴ The independent DataAgentBench project confirms the benchmark's 54-query, multi-database methodology and public submission model, but the crawler-visible current leaderboard did not independently expose that exact Alkera result during this audit.⁷ AiToolMap therefore preserves the 83.28/#1 figure as a vendor/YC-repeated claim rather than using it as a numeric rating input. The fixed 50-source panel produced no qualifying exact-product evidence, and missing evidence remains neutral under Rating v1.0.

Alkera is best suited to mature data teams whose work spans multiple warehouses, dbt/orchestration layers and BI destinations, where a change can have hidden downstream impact. Lineage-aware reasoning, fine-grained action permissions and approval controls are especially relevant for production data engineering and governed analytics.¹³

It is less suitable for small teams with a single simple database, buyers that require transparent self-serve pricing, or organizations that need completed third-party certifications before adoption. Teams considering sensitive data should validate the exact deployment mode, retention configuration, model-provider path and customer-specific compliance documentation before production use.³⁶