Agentic Index
Day AI vs HubSpot (2026)
Day.ai and HubSpot frame the AI native challenger versus incumbent CRM question: Day is a CRM rebuilt around AI from scratch, capturing and organizing customer context automatically, with a pricing page whose rates were not retrievable and third party estimates conflicting between about thirty dollars per user and custom pricing above one hundred, while HubSpot layers Breeze agents on its established platform with outcome pricing, fifty cents per resolved conversation and a dollar per qualified lead, requiring a Professional or Enterprise Hub. Startups betting on an AI first CRM evaluate Day; teams on HubSpot get agent leverage without migration.
| At a glance | Day AI | HubSpot |
|---|---|---|
| Category | GTM / revenue agent | GTM / revenue agent |
| Entry price | Pricing page exists but rates were not retrievable; third party estimates conflict, from about thirty dollars per user per month to custom pricing above one hundred dollars per user | Outcome-based · $0.50/resolved convo, $1/qualified lead |
| Free / trial | One third party review describes a limited preview tier; not confirmed on retrieved official pages | — |
| Pricing confidence | contact only | public partial |
| Feature |
D
Day AI
|
H
HubSpot
|
|---|---|---|
| Action & orchestration | ||
|
Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
Full / Explicit | Full / Explicit |
|
Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
Full / Explicit | Full / Explicit |
|
Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
Full / Explicit | Full / Explicit |
| Knowledge & context | ||
|
Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
Full / Explicit | Full / Explicit |
|
Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
Full / Explicit | Full / Explicit |
| Control & trust | ||
|
Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
Full / Explicit | Partial |
|
Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
Partial | Full / Explicit |
|
Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
Partial | Full / Explicit |
|
Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
No / Not documented | Unknown / Unspecified |
| Solution readiness | ||
|
Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
Full / Explicit | Full / Explicit |
| Platform extensibility | ||
|
Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
No / Not documented | Partial |
|
APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
No / Not documented | Full / Explicit |
|
Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
No / Not documented | Partial |
| Specialist automation | ||
|
Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
No / Not documented | No / Not documented |
Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing |
D
Day AI
|
H
HubSpot
|
|---|---|---|
|
Entry price Lowest public entry point |
Pricing page exists but rates were not retrievable; third party estimates conflict, from about thirty dollars per user per month to custom pricing above one hundred dollars per user | Outcome-based · $0.50/resolved convo, $1/qualified lead |
|
Pricing confidence How public the numbers are |
Contact only | Public — partial |
|
Billing Primary billing axis |
per user subscription per conflicting third party estimates; official structure not retrieved | resolutions |
|
Variable cost Workload / overage exposure |
Medium variable cost | High variable cost |
|
Free tier / trial Try before you buy |
No free tier
|
Free tierTrial
|
|
Buying motion Self-serve vs sales call |
Mixed | Mixed |
Choose Day AI if
- An AI native CRM without legacy data entry is the bet you want to make.
- Automatic context capture beats configuring a traditional CRM.
- You are early enough that CRM migration cost is trivial.
Choose HubSpot if
- Your CRM gravity is already HubSpot and agents extend it.
- Outcome pricing per conversation and lead ties spend to results.
- A mature ecosystem and support organization derisk the platform.
Day.ai's public rates were not retrievable and third party estimates conflict. Confirm current per user pricing directly.