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Day AI Review 2026: Company Memory, GTM Agents & Pricing
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
Recently Updated
Who should use this?
Revenue teams that need shared context across calls, email, calendar, and CRM work and Operations leaders deploying repeatable, role-specific GTM agents.
Who should avoid it?
Organizations that cannot map source permissions before ingestion, Teams wanting a conventional CRM with minimal process change
What problem does it solve?
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.
Would I recommend it?
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.
Advisor score
8.2/10
Premium review framework
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.
Direct 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.
What to verify
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.
Personal Recommendation
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.
Try the recommendation
See whether Day AI belongs in your stack
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.
Overall Score
8.2/10
Research Based
- Last reviewed
- Sep 23, 2026
- Last updated
- Sep 23, 2026
Editorial Review Framework
How Day AI scores
Recently Updated
Who should use this?
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.
Who should avoid it?
Organizations that cannot map source permissions before ingestion, Teams wanting a conventional CRM with minimal process change
What problem does it solve?
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.
Would I recommend it?
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.
Overall Score
8.2
Ease of Use
8.4
AI Quality
8.2
Features
8.4
Speed
8.0
Integrations
8.2
Value for Money
8.0
Customer Support
7.8
Learning Curve
8.0
Recommended 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
Not Recommended For
- 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
Recommended Because…
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.
Scores use a 0-10 editorial scale. The source data is maintained as 5-point review dimensions, then normalized for reader-friendly comparison.
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.
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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: Complete three to five representative tasks with known acceptable outcomes and compare them with your current process.
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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Product interface evidence
Evaluation
Research-based
Price posture
From $0/month
Reviewed
2026-09-23
No authentic product screenshot is published for this review. DiscoverAI does not use generated interface images as product evidence.
Pricing
Freemium
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.
Free plan: 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.
Editorial freshness
Checked this month
Pricing and material product claims were checked September 23, 2026.
Pros & Cons
Pros
- Revenue teams that need shared context across calls, email, calendar, and CRM work
- Permission-aware context graph
- A bounded pilot can test value before broad rollout
Cons
- Organizations that cannot map source permissions before ingestion
- Teams wanting a conventional CRM with minimal process change
- Pricing, limits, and product behavior can change
Best For
Revenue teams that need shared context across calls, email, calendar, and CRM workOperations leaders deploying repeatable, role-specific GTM agentsTeams prepared to govern write actions and shared customer memory
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.
No approved community evidence yet. Be the first verified user to contribute.
Key Features
- 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
Integrations
- Gmail
- Google Calendar
- Slack
- Gong
- Snowflake
- API and MCP
FAQs
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.
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