Day AI Review 2026: Company Memory, GTM Agents & Pricing
A research-based review of Day AI's capabilities, economics, data boundaries, and operational fit.
Bottom line
Day AI combines permission-aware company memory with role-based agents that can prepare meetings, draft follow-ups, manage pipeline work, and run scheduled go-to-market tasks.
Editorial accountability
Who checked this guide
- Evaluation type
- Hands-on evaluation
- Last materially checked
- Evidence
- 4 listed sources
Hands-on testing is identified explicitly. Research-based coverage uses cited product documentation and other named sources; it does not imply every paid plan was used. Read the full methodology.
Editorial freshness
Pricing and material product claims were checked September 23, 2026.
Review evidence
What this guidance is based on
- Review type
- Research-based product assessment
- Material review date
- September 23, 2026
- Evidence
- First-party product, pricing, documentation, privacy, and security material
- Buyer test
- Controlled quality, cost, permissions, and failure-path evaluation
Important limits
- • DiscoverAI did not complete a long-term paid deployment.
- • Features, prices, limits, and data practices can change.
In this guide
Short answer
Day AI is a compelling pilot for revenue teams whose real bottleneck is fragmented customer context rather than another isolated assistant. Its upside comes from shared memory plus repeatable agent behavior; its risk comes from giving one system broad read and write access. Buy only after validating permission inheritance, record accuracy, approval gates, auditability, and measurable pipeline work saved.
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Best for
- Revenue teams that need shared context across calls, email, calendar, and CRM work
- Operations leaders deploying repeatable, role-specific GTM agents
- Teams prepared to govern write actions and shared customer memory
Look elsewhere if
- Organizations that cannot map source permissions before ingestion
- Teams wanting a conventional CRM with minimal process change
- Buyers unwilling to test automated actions against a system of record
What Day AI does
Day AI combines permission-aware company memory with role-based agents that can prepare meetings, draft follow-ups, manage pipeline work, and run scheduled go-to-market tasks. Its documented capabilities include Permission-aware context graph, Role-based AI agents, Meeting capture and preparation, Pipeline and opportunity management, Scheduled and event-triggered skills, Audit trails and approval controls.
Pricing and total cost
Day AI lists Free at $0, Turbo at $24 per agent monthly, Professional at $60, and Executive at $200 when billed annually. It charges for deployed agents rather than every human seat; automated skill slots, pipeline tools, prospecting, workspace controls, billing cadence, and volume discounts determine the actual cost.
Yes. Free users can ingest Gmail and Calendar data, record meetings, search shared customer memory, create contacts, and add workspace notes, but receive no automated skill slots.
Privacy, security, and governance
Map every source the product can read, every system it can write to, how permissions carry across, what is retained, which model providers process data, how consent works, and how exports and deletion behave. Use least privilege, preserve a system of record, and require human approval for consequential actions until real error rates are known.
A fair buyer test
Pilot one read-heavy agent and one bounded write agent with a small revenue pod for 30 days. Seed conflicting contacts, stale opportunities, restricted conversations, duplicate companies, changed owners, and revoked users. Measure retrieval precision, incorrect merges, missed context, unauthorized exposure, draft acceptance, write-back errors, correction time, agent cost, and hours of approved work saved.
Alternatives to compare
Compare Day AI with close, hubspot, salesforce einstein using the same tasks, source data, reviewers, and success thresholds. Feature lists are less useful than accepted outcomes, failure severity, correction time, governance fit, and total cost.
Final verdict
Day AI is a compelling pilot for revenue teams whose real bottleneck is fragmented customer context rather than another isolated assistant. Its upside comes from shared memory plus repeatable agent behavior; its risk comes from giving one system broad read and write access. Buy only after validating permission inheritance, record accuracy, approval gates, auditability, and measurable pipeline work saved.
This is a research-based assessment, not a claim of long-term paid deployment. Features, prices, limits, and policies were checked against first-party sources on September 23, 2026 and can change.
Reusable trial worksheet
Test Day AI before you commit
Turn this review’s buyer test into evidence. Your entries autosave only in this browser and are never added to shared shortlist links.
Confirm the tool meets every must-have workflow and stakeholder requirement.
Review starting point: Revenue teams that need shared context across calls, email, calendar, and CRM work; Operations leaders deploying repeatable, role-specific GTM agents; Teams prepared to govern write actions and shared customer memory
Run the same representative work you would use in production; do not score a polished demo.
Review starting point: Pilot one read-heavy agent and one bounded write agent with a small revenue pod for 30 days. Seed conflicting contacts, stale opportunities, restricted conversations, duplicate companies, changed owners, and revoked users. Measure retrieval precision, incorrect merges, missed context, unauthorized exposure, draft acceptance, write-back errors, correction time, agent cost, and hours of approved work saved.
Calculate the effective cost per accepted result, including usage, review, corrections, and required add-ons.
Review starting point: Day AI lists Free at $0, Turbo at $24 per agent monthly, Professional at $60, and Executive at $200 when billed annually. It charges for deployed agents rather than every human seat; automated skill slots, pipeline tools, prospecting, workspace controls, billing cadence, and volume discounts determine the actual cost.
Define an acceptance threshold, test known answers and edge cases, and record every correction.
Review starting point: Editorial quality signals: features 4.2/5; AI quality 4.1/5. Validate these signals in your own work.
Verify what data enters the product, who can access it, how long it is retained, and whether it trains models.
Review starting point: Use approved low-risk data first. Check roles, consent, deletion, subprocessors, model-training settings, and the contract—not only the marketing page.
Test the real handoffs, permissions, failure states, and export path your team depends on.
Review starting point: Gmail, Google Calendar, Slack, Gong, Snowflake, API and MCP
Record training, governance, reliability, accessibility, ownership, and change-management risks before rollout.
Review starting point: Organizations that cannot map source permissions before ingestion; Teams wanting a conventional CRM with minimal process change; Pricing, limits, and product behavior can change
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Community evidence
How verified users put Day AI to work
Structured, editor-moderated experience—not star ratings. This complements our independent review and never changes its score.
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Sources and verification
Product details and claims were checked against the following primary sources.
Frequently asked questions
What is Day AI?
Day AI combines permission-aware company memory with role-based agents that can prepare meetings, draft follow-ups, manage pipeline work, and run scheduled go-to-market tasks.
How much does Day AI cost?
Day AI lists Free at $0, Turbo at $24 per agent monthly, Professional at $60, and Executive at $200 when billed annually. It charges for deployed agents rather than every human seat; automated skill slots, pipeline tools, prospecting, workspace controls, billing cadence, and volume discounts determine the actual cost.
Who should use Day AI?
Revenue teams that need shared context across calls, email, calendar, and CRM work, Operations leaders deploying repeatable, role-specific GTM agents, Teams prepared to govern write actions and shared customer memory.
How should buyers test Day AI?
Pilot one read-heavy agent and one bounded write agent with a small revenue pod for 30 days. Seed conflicting contacts, stale opportunities, restricted conversations, duplicate companies, changed owners, and revoked users. Measure retrieval precision, incorrect merges, missed context, unauthorized exposure, draft acceptance, write-back errors, correction time, agent cost, and hours of approved work saved.
Recommended tool
Use Day AI if this workflow fits your team
Day AI is a compelling pilot for revenue teams whose real bottleneck is fragmented customer context rather than another isolated assistant. Its upside comes from shared memory plus repeatable agent behavior; its risk comes from giving one system broad read and write access. Buy only after validating permission inheritance, record accuracy, approval gates, auditability, and measurable pipeline work saved.
Tools mentioned in this article
Day AI
Day AI combines permission-aware company memory with role-based agents that can prepare meetings, draft follow-ups, manage pipeline work, and run scheduled go-to-market tasks
Day AI combines permission-aware company memory with role-based agents that can prepare meetings, draft follow-ups, manage pipeline work, and run scheduled go-to-market tasks.
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