The foundation your AI answers depend on.

Your AI is only as good as the data it reasons on.
60% of AI projects fail to get that right.

Integrate connects 22 live data sources in-place, automatically scores data quality on every column, and builds a governed semantic layer your team validates and locks permanently. Organizations that prioritize semantic modeling increase AI accuracy by 80% and cut the cost of maintaining those tools by 60%. Build that foundation today.

60%

of AI projects abandoned due to bad data foundations

60% of AI projects are abandoned due to lack of AI-ready data. The root cause is almost always the same: fragmented sources, unvalidated metrics, and no single governed definition of truth.

That argument has a cost: delayed decisions, eroded trust between your CFO and CMO, and a data team that exists to reconcile instead of analyze. Integrate exists to end it, permanently.

Data Quality Engine

Your data, graded before the AI ever sees it.

The moment you connect a source, Integrate profiles every column in every table - automatically. No setup, no configuration. A statistically rigorous DQ score is computed before a single dashboard is built or question is asked.

DQ Scoring Formula

Every column receives a 0–100 score built from three dimensions. ID and timestamp columns are weighted 3× heavier - they're structurally critical.

Completeness
50%inverse null rate
Uniqueness
25%cardinality ratio
Compliance
25%inverse noncompliant rate
Formula
DQ = (0.50 × completeness) + (0.25 × uniqueness) + (0.25 × compliance)
Sampled at 16,600 rows · 99% confidence · <1% margin of error

A–F Grade Scale

Table scores roll up from column scores. Grades D and F surface an advisory warning before an AskEdi session - so poor data quality is never silently passed to the AI.

APristine
90–100%
BStrong
75–89%
CAverage
60–74%
DPoor
45–59% Advisory
FFailing
0–44% Advisory

Grades D and F both show an advisory warning before an AskEdi session - cautioning about data reliability. You can still proceed. No grade hard-blocks session creation.

What Gets Profiled Per Column

Seven statistical metrics are computed for every column across every table - automatically, the moment connection succeeds.

Null CountEmpty / null values
Distinct CountUnique value cardinality
NoncompliantDatatype violations
Min ValueNumeric & date columns
Max ValueNumeric & date columns
CategoryDateTime · Scalar · String · List
Top ValuesFrequency distribution
ZERO RAW ROWS STORED — SAMPLE ONLY
16,600-ROW CAP · REPRODUCIBLE SAMPLING
AUTOMATED PROFILING ON CONNECTION

AI Readiness Score

Clean data isn't enough. The AI needs context too.

DQ tells you how healthy your data is. AIR tells you how ready it is for AI. A table can be statistically pristine and still produce unreliable answers if the AI has no idea what its columns mean.

A semantic layer is only valuable if the data inside it is trustworthy. AIR scores tell you exactly that - before AskEdi answers a single question. The foundation is ready when AIR says it is.

Structural Health
DQ Score
× 0.50
null rate · cardinality · compliance
+
Semantic Health
Validation
× 0.50
human-validated descriptions
AIR Score
A–F
0–100
AskEdi weights reasoning accordingly
0.0 pts

Undocumented

Column has no description - the AI has no business context to reason against.

AIR contribution0%
0.2 pts

AI-Generated

LLM produced a description from schema + DQ stats. Useful baseline, not yet trusted.

AIR contribution10%
1.0 pts

Human-Validated

Your team reviewed, edited, and locked the description. Permanently protected from AI overrides.

AIR contribution50%

Sector-Aware Metadata Generation

When the AI generates column descriptions, it knows your industry. A column named amt becomes Transaction Amount in Finance - and Dosage Amount in Healthcare. Business vocabulary is baked in from day one.

Finance
Healthcare
Retail
SaaS
Logistics
+ more
Focus Sector
Not sent in
Private Mode

Semantic Layer

What AskEdi reasons on - not your raw data.

Integrate builds a natural-language documentation layer over your schema. Your team validates it. AskEdi consumes the locked result - so every answer is traceable to business logic your team approved, not an LLM's best guess.

At every step of this process - AI generation, human review, and permanent locking - zero raw rows from your database ever reach the LLM. The AI reasons on schema structure and validated descriptions only. That is the architectural guarantee that makes AskEdi's answers trustworthy.

AI-GeneratedAutomatic

On connection, an async job calls your selected LLM with schema metadata and DQ statistics - never raw rows. Every column gets a natural-language description in seconds.

Human ReviewYour Team

Open the Metadata Viewer to read AI-generated descriptions alongside column statistics. Edit any description inline. Mark it Human Validated when it's right.

Locked ForeverProtected

Human-validated descriptions are permanently marked ai_generated=False. Every future DQ refresh skips them - your institutional knowledge survives schema drift.

Metadata Viewer - public.transactionsAI Insights Active
tx_idUUID
DQ:AAIR:A

Unique identifier for each transaction record.

Validated
tx_amountnumeric(10,2)
DQ:AAIR:A

Settled transaction amount in USD.

Validated
statusvarchar
DQ:BAIR:B

Current transaction lifecycle state (SETTLED, PENDING, FAILED).

AI
created_attimestamptz
DQ:AAIR:D
No description - AIR score penalised
HUMAN-VALIDATED = PERMANENTLY LOCKED, NEVER OVERWRITTEN
AI-GENERATED = RE-EVALUATED ON EACH DQ REFRESH
ZERO RAW ROWS EVER REACH THE LLM

Adaptive AI Compliance Controls

AI Context Without the Privacy Compromise.

Three strict privacy postures determine exactly what context is transmitted to the AI during metadata generation. In all three modes, zero raw customer records are ever transmitted.

Max Compliance

Private Mode

Column names are fully anonymized before reaching the AI. The LLM receives only anonymous aliases, actual table names, SQL data types, and DQ statistics.

Column names anonymized (col_1, col_2...).
Backend reverse-maps aliases post-inference.
Ensures zero schema leakage to external AI.
Recommended

Balanced Mode

The enterprise standard. AI receives actual table and column names, data types, DQ statistics, and your Focus Sector for maximum context without row data.

Real schema names shared for accuracy now.
Focus Sector primes domain vocabulary use.
Ensures zero live row data is transmitted.
Max Intelligence

Full Context Mode

Maximum reasoning power. Adds top-frequency sample values per column on top of Balanced Mode, enabling the AI to understand your unique internal taxonomy.

Balanced context + top categorical values.
Enables taxonomy-aware AI descriptions now.
Ideal for heavily categorical data analysis.
MULTI-SALT AES ENCRYPTION
BYOK: OPENAI, ANTHROPIC, DEEPMIND
ZERO RAW RECORD TRANSMISSION

Observability & Lineage

Always in sync. Always traceable.

Integrate watches your data sources continuously. Schema drift is detected automatically. Every downstream dependency is visible before you make a change - so nothing breaks silently in production.

Automated Schema Drift Detection

A daily background cron targets integrations stale for 7+ days whose underlying data has grown by ≥5%. Schema is re-hashed, new or deleted columns are detected, and all DQ and AIR scores are recalculated - without overwriting any human-validated descriptions.

[cron 02:00 UTC] Scanning stale integrations...
INFO integration prod_postgres - stale 8d · row growth +12.3% → refresh triggered
INFO schema re-hash: 2 new columns detected in public.orders
INFO resampling 16,600 rows (reproducible) · recalculating DQ + AIR...
Human-validated descriptions preserved (4 columns skipped)
Manual refresh rate-limited: once per 24h
Auto-triggered on any credential edit

Live Status Pulse

Real-time badges show exactly what the backend is doing. Editing is disabled while any badge is active.

Profiling
Schema scan in progress
Generating AI Insights
LLM generating descriptions
Refreshing
DQ & AIR recalculating
Active
Live pipeline running

End-to-End Dependency Lineage

Every integration card shows a Powers row - icons and counts for every downstream asset consuming that source. Before you edit or delete anything, you know exactly what breaks. If an active Transform flow run is in progress, deletion is hard-blocked. Otherwise, you see the full impact and choose what to do.

Force-delete soft-removes the integration and all dependent assets simultaneously - nothing is silently orphaned.

prod_postgresActive
Transform Pipelines
5
Visualize Dashboards
8
AskEdi Sessions
12

Your connectors are live. Your data is scored. Your semantic layer is validated and locked. The governed foundation that makes every AI answer trustworthy is ready to build today.

Enterprise Credential Security

Zero Friction. Zero Data Storage.

Designed for regulated industries constrained by strict InfoSec policies. Edilitics secures your credentials while executing computation directly against your infrastructure.

Zero Source Storage

Edilitics never stores customer data rows. Only structural configuration and aggregated semantic statistics are persisted. Your physical records remain entirely within your own native infrastructure for maximum data security.

Multi-Salt AES Encryption

Connection credentials are encrypted at-rest using complex domain-level and user-level salt key isolation. Even in the event of a breach, a single compromised instance cannot decrypt any payloads across independent workspaces.

Non-Destructive Target Validation

When linking a new source, the backend fires asynchronous validation requests verifying connection health, proxy configurations, and SSL enforcement without ever executing any unpredictable or destructive target database queries.

Isolated File Sandboxing

Static flat files uploaded into the module are vaulted immediately within entirely isolated Cloud Storage buckets, triggering aggressive background virus-scan validations prior to any backend metric processing or data profiling.

Every security constraint here enforces one guarantee: zero raw rows ever reach the AI. Architecture, not policy.

Collaboration & Governance

Share access. Never share credentials.

Integrations can be shared with any verified workspace member - they get full analytical access without ever seeing the underlying database credentials. You stay in control of who can modify, share, or delete.

CapabilityOwnerShared
View integration & DQ / AIR scores
Browse schema & table explorer
View AI Insights & metadata
Use as pipeline or AskEdi source
Generate / Refresh AI Insights
Refresh DQ & AIR Scores
Edit connection credentials
Share with additional users
Delete integration

Domain Guard

Sharing is restricted to verified organizational domains. 22 personal and generic email providers are blocked - including Gmail, Yahoo, Outlook, Hotmail, and more. No shared integration can ever be exposed to a non-org account.

Credentials Stay Hidden

Shared users get reuse access at the API level. Credential fields are encrypted and never returned in any shared-user response - not hostname, not password, not connection URL. Access grants capability, not visibility.

Workspace Superadmins

Superadmins can manage all integrations across the organization regardless of creator - view, edit, share, and delete. Every operation is logged with user, timestamp, and action for full audit traceability.

Full audit log + CSV export
Org-wide visibility
COMMON QUESTIONS

Everything you need to know before you decide.

No sales call needed. If you have a question we haven't answered here, reach out directly.

THE NEXT LEVEL

Build your governed data foundation today.

22 live connectors. Automatic Data Quality scoring. AI-generated semantic layer validated by your team. The trust engine that makes every AI answer certain.