Early metric change detection
Detects meaningful performance shifts early so teams can notice metric movement before it reaches a review meeting.
Arcwise
ReclamarArcwise is an AI product for detecting meaningful metric changes and explaining them with data-grounded analysis. It turns warehouse and business-context data into decision-ready reports in app, docs, or slides.
Overview
Arcwise is an AI product for understanding metric movement and turning it into decision-ready analysis. The homepage positions it as a way to find meaningful shifts early, explain why they happened, and help teams decide what to do next.
It connects to a data warehouse and business context such as docs, definitions, and operating logic, then generates grounded explanations and deep-dive reports. The site also says the output can live in the Arcwise app or be embedded directly in docs and slides, which makes it useful for teams that want analysis inside existing working surfaces.
Features
Decision-focused insights
Turns metric changes into clear, decision-oriented explanations rather than leaving users with an unexplained spike or dip.
Explainable, auditable AI
Produces explanations that are grounded in connected data and documentation and described as hallucination-free on the homepage.
Business-context ingestion
Uses connected business context such as docs, definitions, and operating logic so explanations can reflect how the organization actually works.
Embedded workflow delivery
Delivers reports inside the Arcwise app or embeds them in docs and slides, so insights can fit existing workflows.
Warehouse and SaaS connectivity
Connects to warehouses and other systems, and the data policy says warehouse pulls are executed as SQL queries while SaaS systems are accessed via API calls.
Use Cases
Spot important metric movements
Analysts and operators can monitor key metrics and quickly see which changes are meaningful, instead of manually combing through dashboards after every shift.
Prepare management-ready explanations
Teams that need to explain a change to leadership can use Arcwise’s traced, data-grounded output to turn a movement into a decision-ready report.
Use internal context in analysis
Companies that keep operating context in documents can connect definitions, rules, and playbooks so the system can reference how the business works when generating analysis.
Embed insights in existing workflow
Organizations that work inside docs and slides can deliver reports where stakeholders already review material, instead of moving them into a separate analysis tool.
Pros and Cons
Pros
- Explains metric changes instead of only surfacing alerts.
- Uses connected business context to keep explanations grounded in organizational definitions and operating logic.
- Supports embedded delivery in docs and slides as well as the app itself.
- States that warehouse pulls and SaaS access are handled without persisting pulled data on Arcwise servers.
- Publishes privacy and data-policy details, including SOC 2 Type II and GDPR statements.
Cons
- Pricing is not published on the site; the pricing URL returns a 404 page.
- The source does not show a full integrations catalog, so some supported systems are only mentioned in the privacy and data policies.
- The homepage does not provide a detailed product walkthrough or implementation limits.
FAQ
What does Arcwise do?
Arcwise connects to your data warehouse and business context, then generates explained metric movements and decision-ready reports. The site says the output can be used in the Arcwise app or embedded in docs and slides.
Which systems can Arcwise connect to?
The site explicitly mentions Snowflake, BigQuery, and Databricks, and says it can also connect to business context such as docs, definitions, and operating logic. The data policy adds that Arcwise can work with SaaS systems such as Salesforce, Looker, and NetSuite.
How does Arcwise work with data?
The homepage says Arcwise can surface meaningful metric changes, explain them with traced AI, and deliver deep-dive reports. The data policy says it executes SQL queries on your behalf for warehouses and API calls for SaaS systems, without persisting pulled data on its servers.
How does Arcwise use Google Docs, Slides, and Sheets?
The privacy policy says Google Slides and Sheets content can be extracted for analysis and productivity features, and that Google Docs access can be used to create or update documents with generated reports, summaries, or reference materials. It also says Arcwise does not extract existing Google Docs content unless you explicitly copy or input it into the service.
What security and compliance information is available?
Arcwise says it is SOC 2 Type II compliant and GDPR compliant in its data policy, and its privacy policy says it has been verified by third-party auditors and penetration testers. The data policy also says users authenticate through Google OAuth 2.0.
Quick Facts
- Category
- AI analytics
- Primary workflow
- Metric change detection and explanation
- Output surfaces
- Arcwise app, docs, and slides
- Data sources mentioned
- Snowflake, BigQuery, Databricks, and SaaS systems such as Salesforce, Looker, and NetSuite
- Company
- Archimedes Labs, Inc.
- Source domain
- arcwise.app
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