Everyday is a predictive asset and workflow management platform. It connects your existing tools, reconciles assets, and predicts workflow risks — giving teams, projects, and leaders operational clarity before problems cost millions.

Project management tools like Asana, Monday, or ClickUp focus on task and timeline management. Everyday goes further by providing predictive workflow intelligence, reconciling assets, and automatically generating corrective actions. Everyday works alongside project management tools to prevent project drift and compliance errors.

A DAM manages asset storage and governance, but lacks predictive intelligence. Everyday combines DAM-grade asset management with workflow lifecycle automation. Everyday not only centralizes assets but also prevents duplicates, reconciles metadata, and ties asset usage directly to project outcomes.

No. Everyday complements AI browsers like Dia and Perplexity. While browsers provide research and contextual assistants, Everyday supplies the asset intelligence and workflow context they rely on — ensuring only the right, approved, and compliant assets are used.

Everyday’s predictive AI collects log data from your apps, compares it to your procedural documents (SOPs, briefs, plans), and flags deviations. It predicts potential workflow breakdowns and automatically generates corrective actions and updated project plans.

Everyday ensures asset lifecycle integrity by eliminating duplicates, reconciling metadata, and tracking rights and compliance across tools and teams. It acts as the system of record and system of action for digital assets.

Everyday detects deviations from standard workflows before they escalate. By aligning teams, assets, and tasks in real time, Everyday reduces project drift, accelerates speed-to-market, and prevents compliance errors that can cost millions.

Yes. Everyday integrates with tools like Asana, Monday, Wrike, ClickUp, Notion, Slack, Figma, and Adobe Creative Cloud. Everyday uses OAuth-based connectors to sync log data and map assets without requiring heavy IT lift.

Everyday uses pseudonymized log data, granular RBAC controls, and full audit trails. It also offers human-in-the-loop review toggles for enterprise compliance. Enterprises can bring their own LLMs to keep AI governance in-house.

Yes. Everyday allows you to plug in your own LLM or AI foundation model to power predictive workflows, ensuring compliance with enterprise AI policies.

Yes. Everyday fully anonymizes and pseudonymizes log_data before processing, ensuring privacy and security while still delivering predictive insights.

The Everyday pilot program runs for 3–6 months and includes:

AI Asset Engine → reconciles metadata + asset issues.

AI Ops Lifecycle Manager → fixes operational drift across marketing + creative ops.

Workspace → time tracking, digests, and workflow automation.

Most teams see ROI during the pilot phase, with measurable improvements in speed-to-market, compliance risk reduction, and asset reuse savings within 3–6 months.

Everyday is built for Creative Ops, Marketing Ops, Design Ops, and Enterprise Operations leaders. These teams face the greatest pressure to deliver faster, cheaper, and with full compliance.

Everyday deploys via OAuth API integrations with workflow and asset tools. Pilots require minimal IT resources and expand department-by-department across the enterprise.

Everyday offers a pay-for-outcomes model during pilots and a scalable SaaS model as deployments expand. Pricing aligns with measurable ROI (time saved, compliance risk avoided, speed-to-market gains).

Everyday is a hybrid Service-as-Software + SaaS model. We work with larger organizations on an initial project-based outcomes immediately, and then scales via SaaS deployment for enterprise-wide adoption.