Tilores

Tilores is entity-resolution software for developers who need to reconcile duplicate or conflicting records across systems into unified profiles in real time. It maps, normalizes, and enriches fields such as names, phone numbers, and addresses before applying deterministic rules and fuzzy matching. Matches 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, with webhooks and event streaming also available. IdentityRAG connects Tilores to LangChain and Amazon Bedrock; the company describes it as usable with any LLM through LangChain. Deployment options include managed AWS, a customer's AWS account or another cloud, and on-premise. Tilores Studio stores data locally, with builds for macOS Apple Silicon, Windows x64, and Linux x86_64. Its free local mode allows up to 100,000 records per deployment, but connecting Studio to Tilores Cloud requires a cloud plan. Production pricing is by custom quote.

Tilores combines record preparation, matching, and API access with several deployment choices. The free local mode has a defined record cap, while production pricing requires a custom quote.

Tilores is aimed at developers working on record matching and use cases such as fraud, compliance, Customer 360, and AI. Its local Studio mode may suit people who want to evaluate person and company matching on their own computer.

Overview

Tilores is a developer-focused platform for resolving records about the same person or company across different systems. It is best suited to teams building live applications that need a unified view of an entity; its layered record preparation and explainable matching give it more scope than a simple duplicate-cleanup tool.

Its main trade-off is commitment: production deployment and support are tailored through a custom quote, while free evaluation is local and capped at 100,000 records per deployment. Teams that need a published production price or a manual merge-approval workflow should consider other options.

Key features

Tilores maps, normalizes, and enriches fields such as names, phone numbers, and addresses before comparing records. It combines deterministic rules with fuzzy matching, then supplies explainable links, a quality score, and an audit trail. That combination suits workflows where teams need to understand why records were joined, not just receive a deduplicated result.

Entity retrieval, ranked fuzzy search, and aggregation of source records run through a real-time GraphQL API. Automatic merging and duplicate prevention support ongoing resolution, but the merge review workflow is automatic; teams that require a human approval gate should look elsewhere.

Prebuilt connectors cover Salesforce, HubSpot, and Snowflake, alongside webhooks and event streaming. IdentityRAG connects entity resolution to LangChain and Amazon Bedrock and is described as working with any LLM through LangChain, a useful route for teams incorporating resolved entities into AI applications.

Deployment options include managed AWS, a customer's AWS account or another cloud, and on-premise installation. The pricing page describes managed AWS infrastructure as SOC 2 certified and includes GDPR-compliant data processing. Tilores Studio runs and stores data on the user's computer, with data staying on that machine; its macOS build supports Apple Silicon only, alongside Windows x64 and Linux x86_64 versions.

Pricing

Tilores Studio Local Mode: free. It allows person and company matching without an account or licence key, up to 100,000 records per local deployment. This is a meaningful evaluation option for developers who want to keep data on their computer, but it is not a substitute for cloud production: connecting Studio to a Tilores Cloud deployment requires a cloud plan.

Tilores Production: custom quote, billed according to data volume, deployment model, SLA and compliance needs, and support requirements. Pricing is per Unified Customer Record (UCR), not per raw record or seat, and the full platform is included across deployment models. This can align the quote with the entity-resolution workload, but teams must scope requirements before they can assess the production cost. Support can range from standard technical support to a dedicated customer success engineer.

Tilores has a freemium pricing model and a free plan, but no free trial. Studio's record cap is the key free-plan limit; production pricing is custom rather than a published monthly rate.

Platforms

Tilores supports API, Linux, macOS, self-hosted, web, and Windows. Studio's desktop editions are for macOS Apple Silicon, Windows x64, and Linux x86_64. Cloud and on-premise deployment choices make it relevant to teams with different infrastructure requirements, while the Studio-to-Cloud connection requires a cloud plan.

Who it's for

Tilores is aimed at developers and organizations that need entity resolution embedded in operational systems, including use cases in fraud, compliance, Customer 360, and AI. It is a stronger fit for teams that value real-time API access, explainable matching, and deployment flexibility than for teams looking only for a manual data-cleaning interface or a small, fixed-price production plan.

Pros and cons

• Pro: Record preparation, deterministic and fuzzy matching, and a quality score with an audit trail combine the steps needed to build explainable entity profiles.
• Pro: Real-time GraphQL access, connectors, webhooks, and event streaming support integration into live data flows.
• Pro: Local Studio mode keeps data on the computer and offers a no-account evaluation up to 100,000 records per deployment.
• Con: The local cap and cloud-plan requirement for connecting Studio to Tilores Cloud limit the free option's usefulness for production-scale evaluation.
• Con: Production uses custom pricing per Unified Customer Record, so teams cannot compare a fixed subscription price in advance.
• Con: Automatic merging leaves no manual merge-review step for teams that require human sign-off.
• Con: The macOS Studio build is limited to Apple Silicon.

Alternatives

Data Deduplication Software is a useful category starting point for comparing data-deduplication tools.

Zingg is the stronger candidate for teams seeking a free, open-source option for batch probabilistic matching across millions of records; its Community plan is Linux and self-hosted, while Tilores emphasizes real-time GraphQL access and offers managed deployment.

DataMatch Enterprise is a paid alternative with a free trial and enterprise-grade cleansing and fuzzy matching on millions of records.

Data8 Duplicare is a paid alternative with a free trial and web and Windows platforms.

DQE One Unify is a paid alternative with a free trial and a SaaS plan for curative processing hosted in DQE's cloud.

Plauti Deduplicate offers a free Salesforce version, with full-edition features requiring a trial or custom pricing.

Insycle is a paid web-based alternative with a free trial and annual plans starting at $100 a month for 100,000 records and one Data Management Suite module.

Entify is a free alternative with API, self-hosted, and web platforms.

Workbooks is a web-based CRM alternative with a 30-day free trial.

Verdict

Choose Tilores if you are building developer-led systems that need live, explainable entity resolution, flexible deployment, and a local evaluation path. Its strongest reason to choose it is the combination of record preparation, matching, and real-time API access; its main reason to look elsewhere is the custom production quote, especially if you need predictable pricing or human-reviewed merges.