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Enterprise Data Connectors

Your warehouse, molecularly intelligent

Pull compound libraries from Snowflake, Databricks, BigQuery, or Supabase. Run ADMET predictions and compliance screening across every row. Push enriched results back. Schema discovery and field mapping included — without ETL engineering or new infrastructure.

4Warehouse connectors
46Enrichment tools
Bi-directionalPull → Enrich → Push
Zero ETLNo pipeline code

How it works

Connect, enrich, push back

Snowflake, Databricks, BigQuery, Supabase — connect with credentials or OAuth. Schema discovery introspects your tables and auto-detects the SMILES column. Choose processing tools, preview the cost, and run. Results land back in your warehouse — without writing a single line of pipeline code.

Terminal — pull_from_source

Every row, fully characterized

ADMET predictions, regulatory compliance, drug-likeness, and structural alerts computed for every compound in your library. 31 ML models and 8 regulatory jurisdictions — applied per-row, not per-batch. Each row gets its own complete molecular profile.

ADMET Radar — Aspirin

CC(=O)Oc1ccccc1C(=O)O

AbsorptionDistributionMetabolismExcretionToxicity

85%

Abs

72%

Dis

91%

Met

78%

Exc

64%

Tox

Large libraries, tracked

Enrichment jobs run async for large libraries — up to 10,000 rows per pipeline. Track progress from the jobs dashboard or ask your AI. Credit cost previewed before execution. Full per-molecule audit trail for every pipeline run.

NovoMCP

Compute Jobs

Auto-refresh

Active

2

Completed today

18

Avg runtime

7m

run_molecular_dynamicsRunning
md_7f3a8c
Started 8m ago67% · ~4m
dock_moleculesCompleted
dock_2e91b4
Started 12m ago100% · done
predict_structureRunning
struct_a4f2d1
Started 3m ago34% · ~6m
screen_libraryCompleted
screen_c8e5f9
Started 1h ago100% · done

The enrichment workflow

01

Connect

Add your Snowflake, Databricks, BigQuery, or Supabase credentials. OAuth for BigQuery — no service accounts needed.

02

Discover

Schema introspection finds your tables, columns, and types. The SMILES column is auto-detected. Preview row count and sample data.

03

Preview cost

Choose processing tools — ADMET, compliance, properties, optimization. See the exact credit cost before committing. The estimate doubles as a 21 CFR Part 11 audit artifact.

04

Enrich

Run the pipeline. Every row processed through your selected tools. Results written row-by-row with per-molecule audit logging.

05

Push back

Enriched results land in your destination table — the same warehouse, a different schema, or a new connector entirely.

Connector capabilities

Available on Team and Enterprise tiers.

Snowflake

Account identifier, username, password. Specify warehouse, database, and schema. Full read/write access.

Databricks

Personal access token with workspace URL. Target catalog and schema. Unity Catalog compatible.

BigQuery

OAuth — click "Connect with Google" and authorize. No API keys or service accounts needed. Tokens refresh automatically.

Supabase

Connection string from your project dashboard. Service role key for full access. PostgreSQL-compatible.

Schema discovery

Introspect tables, columns, and types. Auto-detect SMILES columns. Normalize to 5 standard types. Filter by name pattern.

Audit trail

Per-molecule processing log for every pipeline run. SMILES validation, tool results, dispositions, exclusion reasons. 21 CFR Part 11 compliant.

Connect your warehouse

Pull compounds, enrich with molecular intelligence, push results back. Set up in under five minutes.