MDM Implementation
We take Reltio from zero to production — data model, match rules, survivorship logic, integrations, and cutover. Every configuration is calibrated against your actual data, not defaults. Our architects have shipped 50+ Reltio go-lives and know exactly where implementations break when shortcuts are taken.
- Data domain assessment and entity model design
- Match rule configuration calibrated on production data samples
- Survivorship strategy with attribute-level source ranking
Data Integration
Integrations fail quietly — and by the time someone notices, months of bad data have already propagated. We design pipelines that anticipate failure: idempotent loads, dead-letter queues, automatic retries, and monitoring that alerts before the business feels the impact. Whether you're on Informatica IICS, MuleSoft, or custom Python, we've built it against dozens of source system combinations.
- Source system profiling and connectivity mapping
- Real-time and batch pipeline architecture and build
- Snowflake, Databricks, and cloud warehouse integration
Data Quality Engineering
If your stewardship queue keeps growing and your business users don't trust the golden record, your match and survivorship rules need recalibration — not more stewards. We run forensic audits on your Reltio configuration against real production data, identify exactly where false positives and false negatives are occurring, and deliver tuned rules that measurably improve data quality within weeks.
- Match rule forensic audit with false positive/negative root cause
- Threshold recalibration using stratified production data samples
- Survivorship rule redesign by attribute, source, and recency
Managed Services
Reltio doesn't run itself. Match rules drift, data volumes change, integrations break at 2 AM, and version upgrades require regression testing. Our managed services team monitors, tunes, and operates your Reltio environment under defined SLAs — with quarterly optimization reviews that keep the platform performing as your data landscape evolves.
- 24/7 platform health monitoring and incident alerting
- Incident response with tiered SLA commitments
- Monthly data quality and platform performance reporting
AI & AgentFlow
Your data stewards shouldn't spend their days on decisions a machine can make with 95% confidence. We implement Reltio AgentFlow to auto-resolve routine exceptions, intelligently route complex cases, and trigger enrichment exactly when records need it. The result: stewards focus on judgment calls, not triage. Typical deployments reduce manual queue work by 60–80% within 90 days.
- Stewardship workflow analysis and automation candidacy mapping
- AgentFlow architecture, agent build, and confidence threshold tuning
- Integration with existing stewardship queues and escalation paths
Training & Enablement
Generic Reltio training teaches the platform. Our training teaches your platform — configured with your data domains, your match rules, your stewardship workflows, and your integration patterns. Participants leave with skills they apply the next morning. We run separate tracks for stewards, administrators, and architects, each calibrated to the decisions that role actually makes in production.
- Custom curriculum built against your Reltio configuration
- Hands-on lab environments with your data domains
- Separate steward, administrator, and architect tracks
One platform.
No generalist overhead.
Datagist works exclusively in the Reltio ecosystem. Every consultant on your project has deep, current Reltio platform knowledge — not a team that rotates across ten different MDM tools and learned yours last month.
When you hit a complex match configuration problem, a survivorship edge case, or an AgentFlow workflow challenge, the person on your project has solved that exact problem before — on Reltio, in production, under pressure.
See how we deliverNot sure where to start?
Describe your data challenge and where you are in the MDM lifecycle. We'll recommend the right engagement model — honestly, even if it means starting smaller than you expected.
Talk to an expert