Manage Algorithmia ML models with browser-side automation
Use PixieBrix to customize and automate any tool you already use, right in your browser.
3000+ Integrations
AI Automation
SOC 2 & GDPR compliant
Free for individuals. No CC required.
Free for individuals. No CC required.
Try a Popular Automation:
Trusted by Individuals and Enterprises

"PixieBrix has solved one of our hardest operational problems - streamlining communication & product updates across support teams. Tracking and keeping everyone in the loop has yielded better agent performance, customer satisfaction & taken a huge burden off management."

Thatcher Foster

VP, Client Solutions

Top reasons to automate Algorithmia in the browser
Add a point-and-click interface on top of the Algorithmia dashboard so analysts can test deployed models without writing API calls
Build browser automations that export model metrics, version histories, and performance logs from Algorithmia into team wikis or reporting tools with one click
Surface an AI Copilot sidebar that explains model outputs and confidence scores in plain language, helping non-technical stakeholders interpret results
Create standardized model review and approval checklists that overlay the Algorithmia UI, enforcing consistent governance before deployment
Connect model deployment events in Algorithmia to notification channels or ticketing tools in the browser without a middleware layer
Connect Algorithmia to 3000+ tools including internal platforms that lack native integrations. No custom development required.
Integrate Algorithmia with 3000+ apps
Algorithmia frustrations that cost your team hours every week
  • Data scientists must context-switch between Algorithmia, their notebook environment, and collaboration tools to document model performance and share findings with stakeholders
  • Non-technical users (product managers, analysts) cannot easily call or test deployed models without writing API requests, creating a dependency on engineering
  • Teams manually copy model metadata, version notes, and performance metrics out of Algorithmia into reports or presentations, introducing errors and delay
  • Reviewing and approving model deployments requires back-and-forth in separate communication tools without a standardized in-browser workflow
  • Lack of transparency in model decision-making makes it hard for non-experts to understand outputs without dedicated explanation tooling

Chat with AI to create your first custom workflow

Read the model prediction results visible on this page and explain in plain language what the model decided, why it likely made that decision, and what the confidence level means for a non-technical stakeholder.
Based on the model version metadata and performance metrics shown on this page, draft release notes suitable for sharing with a product team, including key changes and any known limitations.
Summarize the model performance metrics shown on this page into an executive-friendly paragraph highlighting accuracy, key improvements over the previous version, and recommended next steps.
Review the batch prediction results on this page and flag any outputs that appear anomalous or fall outside expected confidence thresholds, with a brief explanation for each.
Read the dataset description or schema from this data catalog page and produce a concise summary of the data's key fields, data types, and potential quality issues relevant to model training.
Based on the current model status and metrics visible on this page, draft a brief stakeholder update email explaining the model's current deployment state and any actions needed.

Watch PixieBrix in action

Frequently Asked Questions

PixieBrix is designed for teams that want to move faster without heavy engineering effort. It is commonly used by support teams, operations teams, product teams, and technical teams who need to connect tools, reduce manual work, and ensure the right information reaches the right people at the right time.

PixieBrix is a browser-based automation platform that lets you customize how the tools you already use work together. It allows teams to add context, automate workflows, and create guided experiences across apps like support tools, internal dashboards, and SaaS products without building or maintaining custom integrations.

PixieBrix works by layering automation directly into the browser. It can read data from the page you are viewing, connect to APIs, and trigger actions like sending messages, filling forms, or enriching data in real time. This lets teams automate workflows exactly where work is already happening.

2026 PixieBrix, Inc.