Current State
Fragmented records obscure investment signal
- Source systems disagree on customer, product, and entity naming
- Manual data prep introduces lag before decisions can be made
- Low-confidence records consume analyst time during diligence
AI Infrastructure for Private Equity
TitanStack transforms fragmented portfolio datasets into reliable intelligence that supports faster due diligence, tighter monitoring, and better investment judgment.
TITANSTACK AI
Data prep speed
Hours, not weeks
Entity confidence
Traceable scoring
Operating fit
PE-native workflows
Messy multi-source datasets in PE due diligence and monitoring create avoidable execution drag.
Current State
TitanStack Method
Normalize inconsistent records and collapse duplicates into clean, analysis-ready entities.
Process structured and unstructured source formats in a single ingestion pipeline.
Score record quality and confidence so teams can prioritize review effort intelligently.
Push cleansed outputs directly into existing analytics stacks and reporting systems.
Before/after data transformation view showing raw fragmented records converted into normalized entities.
Processing pipeline diagram from ingestion to normalization to quality validation and export.
Ingest
Map source schema
Cleanse
Resolve entities
Score
Attach confidence
Publish
Ship to BI/warehouse
Integrations across modern data warehouses and BI tooling.
Snowflake
BigQuery
Databricks
Tableau
Power BI
Looker