Day AI vs Lightfield: which one holds up when the whole team uses it
Updated
The short answer. Day AI and Lightfield both build the customer record from your team's email, calendar and meetings, and both run real agents, so the choice comes down to what happens when a whole team, not one founder, relies on what those agents see and do. Day AI is built for that team: every rep gets an agent that works with their own permissions, each person's email rules decide what teammates and agents can read, and RevOps publishes one skill to every agent, in place of your CRM or on top of Salesforce or HubSpot. Like Day AI, Lightfield builds the record from conversations; the difference: Lightfield is one product that replaces your CRM and call recorder, with groups and record permissions on its Enterprise plan (as of October 2026), while Day AI can also run on top of the CRM you already have.
Say you run sales at a B2B payments company with nine reps, and you run Day AI in place of your CRM. It's 5:30 on a Thursday, and you open the pipeline in Day AI. The agent has already created the new deals and moved the ones that earned their next stage. It stopped short of closed-won and closed-lost, because that's the guardrail you set: those two stages are yours to call, and the agent leaves them to you. Your reps already have their end-of-day follow-up drafts waiting in Day AI. Tomorrow morning, each of them starts the day with a briefing from their agent. Nobody on the team typed a stage today, and you know what's going on in the pipeline.
Where the usual comparison goes wrong. Most Day AI vs Lightfield comparisons argue about labels: is it a CRM or a layer, who has more checkmarks. On the features that make the record write itself, the two products overlap a lot. What separates them is the second user: whose email an agent may read, who sets what agents can change without asking, and how one good skill reaches every rep. Day AI provides the context graph and agent control plane to quickly and securely upgrade your company brain, and its view is that agents do the work and people approve it, with guardrails the team sets. If you're comparing these two, you've already decided the record should build itself from conversations, and that was the right call.
Day AI and Lightfield at a glance, as of October 2026
Lightfield facts below come from Lightfield's pricing page and its help center, read in full on 2026-10-30. Day AI facts are from Day AI's product.
| Day AI | Lightfield | |
|---|---|---|
| What it is | A shared record built from your team's conversations, with governed Day AI agents working on it. Run it as your CRM or on top of Salesforce or HubSpot. | An AI-native CRM with its recorder, sequencer and enrichment in the same product (pricing) |
| Where the record comes from | Gmail and Google Calendar, a native notetaker, Gong and Granola history, and Slack from the moment the Day AI app joins a channel. | Email and meetings from Google or Outlook for users with a capture seat, with recording and transcription (pricing FAQ) |
| Email privacy between teammates | Each person sets sharing rules by domain, address or Gmail label. A private rule from any teammate keeps a message private, and one private message keeps its whole thread private. | Each mailbox is Full access or Metadata only, and any item can be made private. Metadata only "can't hide an item that a teammate's Full access account also synced" (help) |
| What an agent can see | A Day AI agent inherits the permissions of the person it works for, so it never answers from a message that person couldn't open. | Automation steps use "the data available to the member it runs as" (help) |
| Who can change records | Every value in Day AI shows its sources, and you can ask the agent what changed and why | Groups and record permissions are on Enterprise; on other plans "Owners, Admins and Members can create and edit every record" (help) |
| Rolling agents out to a team | Admins publish skills from a shared library to every Day AI agent, Managed or Template, with versions you can restore and a learning mode | Automations on Pro, Growth and Enterprise, built by owners and admins, with each publish saved as a version and drafts held "For review" (help) |
| Salesforce and HubSpot | Day AI runs in their place, or on top through their MCP servers, which allow reads and writes when the write tools are turned on, each person under their own login | HubSpot sync "runs one way, from HubSpot to Lightfield" on Pro and up (help); bi-directional CRM sync on Enterprise (pricing) |
| Building on it | Day AI's graph over MCP (Turbo and up) and the MIT-licensed Day AI SDK | An API, an MCP server on every plan, a CLI, and Python, TypeScript and Go quickstarts (API guides, Claude setup) |
| Pricing | Per agent, in three tiers (Turbo, Professional, Executive), monthly or annual, with at least one Professional or Executive agent per workspace. No usage-based pricing. Current prices on day.ai/pricing. | Starter per user for small teams; Pro and Growth per workspace, billed annually, with workspace credits; Enterprise custom (pricing) |
Where Lightfield is strong, and where Day AI fits
Lightfield has real agents. Its recorder is built in, and builders get an API, an MCP server, a CLI and SDK quickstarts. Like Day AI, Lightfield builds the record from conversations; the difference: below Enterprise, Lightfield's HubSpot sync runs one way, from HubSpot to Lightfield, while Day AI can run on top of Salesforce or HubSpot and write back to them when the write tools are turned on.
Day AI fits when the record has to work for more than one person. That's where most of the work in a go-to-market system ends up: a second rep with different email rules, a RevOps lead who has to ship the same skill to twenty agents, a sales leader who wants agents moving stages but not closing deals. Day AI is built around those jobs, and it lets you keep Salesforce or HubSpot for as long as you like.
The second-user test, run in Day AI
The fastest way to compare any two AI tools that build the customer record is to stop testing them alone. Put a second person on the same record and ask five questions. Each one below says what it checks and what Day AI does for it.
- Whose email can my agent read? Two reps share a customer, and one keeps a thread private. In Day AI, the private rule wins: a private rule from any teammate keeps the message private, and the agent inherits its person's permissions, so it can't answer from a thread its person couldn't open.
- What can an agent change without asking? Write the rule down. In Day AI, an agent keeps a memory of the standing rules its person gives it ("never move a deal to closed-won"), and a skill can start in learning mode, reporting what it would have done before it is allowed to act.
- How does one good skill reach every rep? In Day AI, an admin publishes it from the shared library as Managed (every agent follows the source) or Template (each agent gets a copy to tune). Every skill prompt is versioned, so you can restore an earlier version.
- Can I see why a value changed? In Day AI, every value shows its sources, and you can ask the agent what changed and why. Answers cite the call clip or the message they came from.
- Can I keep my current CRM while I decide? In Day AI, you can run on top of Salesforce or HubSpot through their MCP servers, or in their place; nothing forces a cutover date.
How to run a two-week evaluation in Day AI
Two weeks is enough to answer the five questions above with your own accounts and two reps in Day AI.
Step 1: Connect two reps' email and calendar to Day AI
Have two reps who share accounts each connect Gmail and Google Calendar to Day AI. The first sync finishes within hours, and from then on the agents work from your history. Before they connect, each rep sets sharing rules: share everything or nothing by default, with exceptions by domain, address or Gmail label.
Step 2: Bring in your meetings in Day AI
Turn on Day AI's notetaker, or connect Gong or Granola so your call history comes in with transcripts. If the team works in Slack, add the Day AI app to the channels where deals get discussed; it reads from the moment it joins.
Step 3: Decide where the record lives in Day AI
Pick one. Run Day AI as your CRM, with pipeline, contacts and companies kept current from conversations. Or connect the Salesforce or HubSpot MCP, each person with their own login, and allow its write tools so agents can update stages, notes and fields after a call. Without write tools, Day AI reads only.
Step 4: Give each rep a Day AI agent and one shared skill
Give each rep an agent with a name, a job and the person it reports to. Publish one skill to both agents as Managed, for example a follow-up draft after every recorded call, and start it in learning mode. Tell each agent its standing rules, such as which stages it may move on its own. When the skill leaves learning mode, each rep reviews the follow-up draft in Day AI before it goes out, or replies with a correction.
Step 5: Run the second-user test in Day AI
Have rep B ask their agent about a thread rep A kept private, and confirm it doesn't answer from it. Open a deal field the agent changed, check its sources, and ask the agent what changed and why. Reply to an agent's draft with a correction and check that later runs follow it. For a structured version, run the open-source evaluation skill in Claude Code: npx skills add day-ai/company-brain-evaluation.
Where a single-player setup breaks
Any AI tool that builds the customer record works well for the one person who set it up. These are the places it strains when the team grows, whichever product you choose.
- Email defaults that were fine for one inbox. When the founder was the only user, "share everything" cost nothing. With a second rep, one person's setting can expose another's thread. In Day AI, the most private setting wins, and one private message keeps the whole thread private.
- Every automation built by one admin. The founder writes the follow-up rule, and every new rep inherits a copy nobody maintains. In Day AI, a Managed skill keeps every agent on the source version, and a Template lets each rep tune their own copy.
- Agents that act before anyone trusts them. Turn on an agent that moves deals on day one and the first wrong move costs a week of confidence. In Day AI, a skill can start in learning mode and earn the right to act.
- Fields nobody can explain. A stage changed overnight and no one knows whether a rep or the model did it. In Day AI, every value shows its sources, and you can ask the agent what changed and why.
- A migration that has to happen all at once. A replacement CRM asks for a cutover date. In Day AI, you can keep Salesforce or HubSpot, run on top through their MCP servers, and move when you're ready.