Entify vs Tilores
Entify
github.com
Tilores
tilores.ioSide by side
| Figure | Entify | Tilores |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 4 |
| Spec score · Data Deduplication Software | 8.4 (#2) | 8.3 (#5) |
| Deployment | It can run locally with Docker or with Python 3.11+ and Node 20+; the README identifies FastAPI, Splink 4, DuckDB, and Next.js in its stack. | Tilores offers managed AWS, deployment in a customer's AWS account or another cloud, and on-premise deployment. |
| Integrations | Optional sign-in and shared storage use Clerk authentication and Supabase persistence. | The production platform lists prebuilt Salesforce, HubSpot and Snowflake connectors plus webhooks and event streaming. |
| Intended users | The project describes itself as intended to make record linkage usable by data stewards and teams without specialist record-linkage expertise. | The company describes Tilores as infrastructure for developers and presents use cases including fraud, compliance, Customer 360, and AI. |
| Matching | It supports exact, Jaro-Winkler, Jaccard, and Levenshtein comparisons, with semantic blocking available as an optional extra. | The platform combines deterministic rules and fuzzy matching, with explainable links, a quality score, and an audit trail. |
| Purpose | Entify is an early open-source workspace for entity resolution, record linkage, and data deduplication. | Tilores resolves duplicate and conflicting records across systems into unified entity profiles in real time. |
Plans
Tilores
- Tilores StudioFree
- Tilores Studio Local ModeFree
- Production TiloresPriced on request
- Tilores ProductionPriced on request
In their own words
Entify
Entify is a free, open-source workspace for linking records, resolving entities, and deduplicating datasets. It uses Splink 4 and DuckDB for matching, with exact, Jaro-Winkler, Jaccard, and Levenshtein comparisons. Automatic setup estimates column types, proposes blocking rules, and explains its choices for users to adjust. It reads CSV, TSV, Parquet, JSON, and Excel files, and reports row counts, distinct values, and completeness by column. Review tools include match evidence, score and threshold analysis, and PDF audit reports. Merge exports keep one surviving record per entity and retain source IDs for tracing or undoing merges. Entify runs locally with Docker or with Python 3.11+ and Node 20+; demo mode works without optional sign-in or shared storage. Its Docker quickstart needs no accounts, API keys, or external services, and uploaded data stays on the machine. The project is intended for data stewards and teams without specialist record-linkage expertise. Optional semantic blocking requires an extra install of roughly 600 MB of Torch dependencies.
Tilores
Tilores resolves duplicate and conflicting records into unified entity profiles in real time. It maps, normalizes, and enriches fields such as names, phone numbers, and addresses before applying deterministic rules and fuzzy matching. Results can include explainable links, a quality score, and an audit trail. A real-time GraphQL API supports entity retrieval, ranked fuzzy searches, and aggregation of source records. Listed connectors include Salesforce, HubSpot, and Snowflake, alongside webhooks and event streaming. Deployment options include managed AWS, a customer's AWS account or another cloud, and on-premise installations. Developers can connect entity resolution to LangChain and Amazon Bedrock through IdentityRAG; the company says it works with any LLM through LangChain. Tilores Studio runs locally on macOS Apple Silicon, Windows x64, or Linux x86_64, storing data on the user's computer. Its free local mode allows up to 100,000 records per deployment. Production pricing is by custom quote, based on data volume, deployment, service requirements, and support.