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Fidence

The prediction layer for your data and agents

View in the Claude registry
Integration details

Description

Fidence is the prediction layer between your company's data and the people and agents that act on it. Connect Fidence to Claude and you can turn your own data into a custom predictive model, score every record, and push the scores back into the tools where work happens, all from one conversation. What you can do: - Bring your data: connect HubSpot, Salesforce, Snowflake, Databricks or monday.com in the Fidence app, and the datasets you import there are ready to train on and score from Claude. monday.com boards can also be imported straight from Claude. - Build a model on your own data: churn, lead scoring, customer lifetime value, fraud, demand forecasting and upsell. Start from a ready template, or point Fidence at your own dataset and target column. - See who is at risk and why: ranked scores with risk tiers, model quality (ROC AUC, precision, recall) and the features that drive the predictions. - Ask Fidence: questions like "which customers are most likely to leave next month and what do they have in common" go to Fidence's own analysis, with suggested follow-ups. - Write back: preview first, then put the scores where work happens: into monday.com boards straight from Claude, or into your CRM or warehouse from the Fidence app, so your automations and agents can act on them. Write-back always asks for confirmation. Every model is trained only on your data, stays in your workspace, and reports its metrics and provenance so you can judge it before you rely on it. Scores show pseudonymous ids by default; full rows need your confirmation. Requires a Fidence account (sign in with Google at fidence-ai.com).

Integration type
Connector
Verification status
Community connector
Platform
Claude
Category
Data & Analytics

The broad Category that contains the Primary Subcategory.

Primary Subcategory
Self-Serve BI & Conversational Analytics

The Primary Subcategory used for this profile’s headline score.

Secondary Subcategories
None listed

Other Subcategories where the Integration is listed.

Brand
Fidence
Access
Account required
First tracked
2026-09-25
Tool count
16
Geography
US

Claude Discoverability Score

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Primary Subcategory
24 scoredVerified connectors by score · Community connectors A–Z
Primary Subcategory
1Omni Analytics71/100
2Polar Analytics61/100
3Google Cloud BigQuery33/100
4dbt25/100
5Amplitude19/100
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Tools

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What are Fidence alternatives on Claude?

As of 2026-09-26, Fidence competes with Omni Analytics, Polar Analytics, Google Cloud BigQuery, dbt, Amplitude, Mixpanel, Snowflake, Supermetrics Marketing Analytics, Adobe Customer Journey Analytics, Aleph, DataHub, PostHog, Funnel, Fullstory, Supabase, Datadog, ChartMogul, Metabase, Hex, Flourish, Gainsight (Customer Communities), Orion by Gravity, Sigma, ThoughtSpot Spotter, Adzviser ActiveCampaign, Adzviser Amazon Seller Central, Adzviser Amazon Vendor Central, Adzviser BigCommerce, Adzviser CallRail, Adzviser CallTrackingMetrics, Adzviser Google Analytics, Adzviser HubSpot, Adzviser Klaviyo, Adzviser Mailchimp, Adzviser Matomo, Adzviser Pipedrive, Adzviser Shopify, Adzviser Sprout Social, Adzviser TikTok Shop, Adzviser WooCommerce, Adzviser Zoho CRM, AlterVision, Basedash, BEEM, Blaze SQL, Bloom Profit Analytics, BOCP - Business Online Control Panel, Cayra MCP, Charts by Szum, contextflo, Credible, Cube, Databox, Evidence Studio, forecast-coach.us-west.pmcp.run, Geckoboard, Jenner Analytics, Juicy attribution & profit, Loam Data, Margins, mcp.adeci.pt, mcp.hologrow.ai, New Vintage, Normalic Assistant, Notehub, Omnivio Lens, OWOX Data Marts, Pagos, Protobi Claude MCP, Rill, Signara, Sprucely.io, Steep, Supernova, Tableau Cloud, Triple Whale, TrueGradient, TuSistema, Upsolve AI, Windsor.ai for Web Analytics, WitCloud, Wren AI, YourBI, 댓글몽 in Claude Self-Serve BI & Conversational Analytics, ranked by public Discoverability Score.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.