Everything you need to run trusted data at scale
Master Data Management, Data Quality, ETL, Orchestration and BI on one platform — so your golden records feed straight into the pipelines, workflows and dashboards that use them.
One flow, from source system to decision
Data enters once, is mastered once, and every service downstream reads the same golden record.
Your systems
- CRM, ERP, e-commerce
- Files & databases
- Kafka topics
ETL & Orchestrator
- Pipelines, 16 transformations
- Flows & schedules
- Landing & staging
MDM & Data Quality
- Validate & reject
- Match & merge
- Trust & survivorship
One trusted record
- Field-level lineage
- Archived history
- Approvals
Every team
- View 360 & Page Builder
- Insight360 dashboards
- Downstream pipelines
MDM
Turn every source's version of a customer, product, supplier or asset into one golden record — matched, merged and traceable field by field.
- Model business entities; landing, staging and master tables are provisioned for you
- Match plans with exact and fuzzy rules, per-column weights and thresholds
- Survivorship per attribute — most trusted or most recent — set in a trust matrix
- View 360: search, review, merge and unmerge records, with a full audit trail
- Hierarchies over mastered records, with a visual hierarchy canvas
- Reference data areas and configurable business-ID generation
- Search profiles with type-ahead suggestions for stewards
- Streaming intake from Kafka topics, loaded in source-priority order
- Vision
- View 360
- Hierarchies
- Page Builder
Data Quality
Stop bad data before it reaches a golden record, and make sure data that fails a rule can never win a merge.
- Column-level rules: regular expressions, ranges and lookups
- Built-in reject rules at staging and business-entity level
- Trust decay — a failed rule lowers that value's trust score
- Every validation result logged against the record it concerns
- Rejected rows kept aside for review instead of silently dropped
- A Data Quality step you can drop into any pipeline
- Data Quality
- Vision
- Transformations
ETL / Transformations
Design the pipelines that move and reshape your data in a visual designer, then run and inspect them from the same place.
- Visual pipeline designer with an expression editor
- 16 transformations: Aggregator, Data Quality, Expression, Index Job, Joiner, Lookup, Mapper, MDM Step, Normalizer, Rank, Router, Sequence, SQL, Structure Parser, Union and Web Service
- An MDM step that runs load, match and merge inside a pipeline
- Run summaries and workflow logs for every execution
- Unsaved design work restored as a draft if you navigate away
- Transformations
- Explorer
Orchestrator
Coordinate loads, matching and pipelines across every module, and see what ran, when, and what it did.
- Flow designer to chain jobs across modules
- Folder-based flow explorer for large estates
- Flow logs with the detail of every run
- Kafka ingestion health at a glance
- Cancellation and time-outs for long-running loads
- Flow
- Monitor
BI / Insight360
Dashboards that read the same validated golden records your stewards maintain — not an export someone took last month.
- Dashboard designer with a tile canvas and chart tiles
- Calculated fields, joins across sources and dashboard filters
- Version history on every dashboard
- Embed dashboards or share them by link, under the same access rules
- Insight360
What every service runs on
Whichever service you start with, these come with it.
Guided setup
A setup wizard provisions the platform database, your first environment, the administrator account and email — your licence key is its first step.
Isolated environments
DEV, QA and PROD each have their own database and accounts, and a badge on every page says which one you are in.
Migration between environments
Export configuration from one environment and import it into another, item by item, with the outcome of each item reported.
Security & access control
Roles with a role hierarchy, module and object permissions, record-level rules, IP filtering and security policy.
Approval workflows
Send changes through reviewers before they apply, with shared workflows and digest emails.
Single sign-on
Microsoft Entra ID and LDAP, alongside local accounts with lockout and password rules.
Agent-ready, with people still deciding
Connect your own AI agents, or turn on the built-in ones. Every AI feature is off until an administrator turns it on, and nothing an agent suggests changes a record until a person approves it.
MCP server for your agents
Agents and assistants that speak the Model Context Protocol can search golden records, read lineage, check data quality and explain a record — each with its own key, scope and activity log.
Privacy-safe by default
Personal and sensitive columns, and subjects who opted out, are withheld from agents unless an administrator decides otherwise. Answers mark record values as data, so text inside a record can't steer the agent.
Proposals, not edits
Agents with the propose scope can suggest an update, a merge or a flag. Each lands in the approval queue marked "AI suggested" for a steward to accept or reject.
AI match reviewer
Reads borderline pairs in the match queue and leaves a verdict with its reasons on the task. Merge and not-a-match stay a steward's buttons.
Migration explainer
Turns the Informatica migration advisor's findings into a short plan in plain words — what to fix first and why. It sees counts and column names, never business values.
Limits and audit
A per-key record limit per hour, revocable keys, one switch to turn agent access off, and every agent call written to the audit trail.
Ready to see it in action?
Tell us which service you're interested in and we'll set up a walkthrough on a scenario like yours.
