Day AI vs Lightfield
Lightfield built a cockpit for a founder selling solo. Day AI built the system a revenue team runs on.
Both fill the record. Both run agents. Only Day AI was built for the day it’s not just you. The moment a second rep starts selling, you’ll want a different product. One you can trust on your pipeline, because every agent move is logged and permissioned. One where RevOps builds an agent once and deploys it to every rep, locked down or open for them to coach. One where every rep and every agent works from the same live memory. Day AI is that product.
- Every rep and every agent on one live customer memory
- Agents you can trust on the pipeline, with every move logged
- Build an agent once, deploy it to the whole team
- Runs on top of Salesforce or HubSpot, or as your record
30-minute personalized demo with a product expert, not a sales pitch. No credit card, no obligation.
Lightfield is genuinely good. For a founder selling solo.
If you’re a founder still doing most of the selling, Lightfield is an effective tool, and we’ll say so plainly. It captures calls and email, answers hard questions about your customers, runs agents that do real work, and hands you an SDK to build more. Their customers are seed-stage founders and for that stage, it works.
Both products climb the same ladder: the record fills itself, you get answers, and agents produce work. Lightfield climbs it for one person. The question when you go past founder-led selling is what the agents stand on when they need to support a whole team.
What a team of reps needs, and where each product lands.
When you move beyond a single seller, creating the right product gets much more complex. There are a couple of areas where Day and Lightfield are comparable. Everywhere else, the gap isn’t marketing. It’s architecture, and most of what we mark you can check against Lightfield’s own site.
| What a team needs | Day AI | Lightfield |
|---|---|---|
| Governance & control | ||
| Permissions scoped to each rep and each agent | Permission-aware by design, on every plan | SSO and RBAC on the Enterprise tier only |
| Decision lineage, who overrode what, under which rule, when | Full history behind every value | Citations to the source conversation (evidence, not lineage) |
| An audit log of every agent action | What ran, for whom, and what it touched, all logged | Not shown |
| Approval guardrails you set per skill | Drafts-only wherever you want a human to sign off | Agents are directable, but no per-role approval model shown |
| Architecture & performance | ||
| One committed state every rep and agent reads at once, updated live | One shared, permission-aware graph everyone reads live | Builds a world model from your raw memory, but one shared committed state across a whole team is not shown |
| Provenance for AI-generated, derivative data, reconciled into that shared state | Tracked and reconciled in the graph | “Versioned memory” |
| Deploy & scale | ||
| Build an agent once, deploy it to every rep, scoped to their deals | Standing agents with job descriptions and schedules | An SDK to build your own, single-player |
| New hires inherit the team’s memory and a working agent roster on day one | Yes | Memory yes; a deployable team agent roster not shown |
| Run on top of Salesforce or HubSpot, or as your record, on your timeline | Yes | Replace your whole stack |
| Native meeting capture, or connect Gong and Granola | Both | Both |
| Commercial | ||
| Cost that doesn’t climb as your agents do more work | Priced by the agent, for the work done. No per-seat fee, no usage meter | Credit-metered, so the more the agents work, the more you pay |
Lightfield capabilities and pricing verified against lightfield.app on August 20, 2026. Spot something out of date? Tell us and we’ll fix it.
The reason you can let agents work your pipeline: you can answer for every move.
Letting agents touch pipeline is a trust decision, and it’s the decision a team can’t hand-wave. Day captures every enrichment, inference, and human correction with its full history: the value, the confidence, the timestamp, and whether a person overrode the AI, so you can always answer “why do we believe this, and when did it change?”
Decision lineage, not just evidence.
Lightfield cites the source conversation, which is good evidence. Day adds who overrode what, under which rule, and when it changed, the lineage that discounting, deal desk, exceptions, and a forecast you can actually trust all run on.
Permission-aware by design, on every plan.
Every agent and every teammate sees and does only what they’re allowed to, so you can put email and pipeline in front of agents without them overstepping. Lightfield gates SSO and RBAC to its Enterprise tier.
Auditable.
Every agent action is logged: what ran, for whom, what it touched. That’s how you trust agents across a whole team, and how you clear the security review.
One live memory for every rep and every agent.
Single-player AI is easy. The wall is the second rep, and the fifteenth. Both Day and Lightfield build a model of your customers from what actually happened. The difference is what each one treats as canonical. Lightfield holds the raw customer reality as a world model. Day holds a reconciled, permission-aware graph, one committed state that every rep and every agent reads at the same moment.
That committed state is what a team runs on. Build an agent role once and every rep gets the same version, scoped to their own deals. Edit a field or a permission and the change lands in every view and every agent right away. New hires inherit the team’s memory on day one instead of starting from zero. Everyone works from the same picture, so the team is never acting on two versions of the truth at once.
Build an agent once. Deploy it to the whole team.
Lightfield hands you an SDK to build your own agents. That makes one person powerful. It doesn’t solve deploying to reps, catching drift, or evaluating what ran. Day’s agents are standing teammates: each has a job description, a schedule, and skills, and reasons over the reconciled graph scoped to each person’s permissions. RevOps builds the role once and ships it to every rep, locked down where you want approval or open for reps to coach and evolve. Our founder, Christopher, works closely with three every day. Open one to see what it had waiting for him.
Reviews my new-business pipeline every morning and flags the deals where my involvement would actually move them, with a specific action for each. Keeps my opportunities current as things change.
My BDR. Every morning he hunts for CEOs and CPOs who should see Day AI, researches each one, and hands me a prioritized list of demo targets, with a reason they’ll care and a clear way in.
Follows me through my day and mines my meetings for content, maintaining my ideas page, then fleshes the best ones into full drafts by evening. Also works my podcast and speaking pipeline: checking new invitations, prepping me for upcoming shows, and finding warm intros through my network.
What it’s worth, once it’s the whole team.
More capacity per rep
Prospecting, prep, and follow-ups run in the background, so reps spend their time on real conversations. Output scales without scaling headcount.
More deals moved forward
Agents catch the slipping commitment and the stale deal and hand reps finished next steps, so fewer opportunities stall on the way to close.
Faster ramp
New hires inherit the team’s memory and a working roster of agents on day one, so they get productive in days, not quarters.
What Lightfield’s comparison page says. What you can check yourself.
They say
Lightfield’s comparison page says Day AI “pivoted away from CRM” to a memory layer.
Check it yourself
Open Day and look. Pipeline, stages, contacts, accounts, reporting, and forecasting are core product, and hundreds of teams run Day as their complete customer record today. Customer memory is the foundation under that record, not a retreat from it. It’s also why Day can run on top of Salesforce or HubSpot when a team wants to keep them. One product, either mode, your timeline.
They say
They say Day just retrieves and summarizes; real agents execute.
Check it yourself
Day’s agents run standing skills that produce finished work: sourced prospects, follow-ups drafted on the right thread, a cleaned pipeline, all held for review. They reason over a reconciled graph, not a re-read of raw transcripts, so the output carries judgment and every value carries its lineage.
Why us
Built by the person who built the last system of record that scaled.
Day AI’s founder, Christopher O’Donnell, was responsible for HubSpot’s product from 2011 to 2021. He built the Marketing Hub, built the Sales Hub and its CRM in 2014, and built and ran the team that shipped Service Hub and Data Hub. That footprint is, to this day, the product HubSpot ships, the only credible alternative to Salesforce ever built, and it scales from one seat to thousands of teams. Building the system a revenue org runs on, not a tool for a founder selling alone, is the exact problem he has solved before. He has spent the years since ChatGPT launched building the successor to the system of record for the age of agents.
Trusted by teams at B2B companies
Coming from Lightfield? Switching is easier than outgrowing it.
Bring your data.
Day imports contacts, accounts, and history.
Keep what works during the move.
Run Day alongside Salesforce, HubSpot, or Gong. No mid-air cutover.
Hands-on onboarding.
A Day specialist sets up your pipeline, permissions, and first agents with you.
No lock-in.
Your data, your decision. Leave on your terms, with everything exportable.
See Day’s agents work on your own data.
A 30-minute personalized walkthrough with a product expert, not a sales pitch.
Questions scaling teams ask before switching.
Lightfield’s comparison page says Day AI “pivoted away from CRM” to a memory layer. Is that true?+
No. Pipeline, stages, contacts, accounts, reporting, and forecasting are all core product, and hundreds of teams run Day as their complete customer record today. That is everything teams use a CRM for, without the data entry. Customer memory is the foundation that makes that record trustworthy, and it is also why Day can run as a layer on top of Salesforce or HubSpot when a team wants to keep them. One product, either mode, on your timeline.
Both tools capture everything and run agents now. What actually differs for a team?+
The difference shows up the moment it is not just one person. Day keeps every rep and every agent working from one reconciled, permission-aware memory, so they never act on conflicting pictures. You can let agents touch the pipeline because every action is logged and scoped. And RevOps can build an agent once and deploy it to every rep, locked down or open for them to coach. Lightfield is built around early-stage teams. It gates SSO and RBAC to its Enterprise tier, and it hands you an SDK to build your own agents rather than a way to deploy them across a team.
Isn’t Lightfield the “real” AI-native architecture, and Day just CRM + AI?+
Both build a world model of your customers, and they choose different things as canonical. Lightfield’s canonical layer is the raw customer reality. Day’s is a reconciled decision graph, how your org applied rules, made exceptions, and changed state over time, held in a live, permission-aware layer that every rep and agent reads at once. For one founder selling solo, a world model over raw memory is fine. For a team, a shared committed state is what keeps everyone on one picture and lets you prove what an agent did.
How do I trust agents to act on my pipeline?+
Day records the full history behind every value, confidence, timestamps, and whether a human overrode the AI, plus an audit log of every agent action, scoped to each person’s permissions. You can always see what an agent did and why, and set “drafts only” boundaries wherever you want a human to approve. That is the difference between a citation to a source (evidence) and decision lineage (who changed what, under which rule, when).
We want schema-less so we don’t configure a CRM. Doesn’t Lightfield win there?+
Capturing everything first and structuring it whenever you want, schema-less and retroactive, is core to how Day AI was built. Add a property today and Day goes back through every conversation you’ve already had and fills it in. Both products do a version of this. The difference shows at scale. A 50-person org needs one shared, stable graph every rep and agent can rely on, held as one committed state the whole team reads. You keep the flexibility, and Day adds views and relationships as you evolve, on top of a graph that stays consistent for the whole team.
How does pricing compare?+
Lightfield moved to usage-based pricing. Seats are unlimited and you pay by credits, so the more work the agents do, the more you pay. Day is priced by the agent and the work it does, not by headcount, with no per-seat fee and no usage meter on the agents, so the cost does not climb as they take on more. For Lightfield’s current credit rates, see their pricing page.
Do I have to replace Salesforce or HubSpot?+
No. Day runs alongside them or replaces them on your timeline. Lightfield is replace-only.
What is Day AI?+
Day AI is the customer memory and agent platform for go-to-market teams. Even the best CRM only holds a fraction of what actually happened with your customers. Day AI is what comes after CRM. It builds a self-updating customer record from every meeting, email, and call, and runs governed agents that create finished work on top of it, with every fact and every action traced to source conversations. It does everything teams use a CRM for, without the data entry, and does what a CRM never could. Agents prospect, prep every meeting, draft follow-ups, keep the pipeline clean, and much more, giving every rep added selling capacity that used to require hiring additional people. It runs as a layer on top of Salesforce or HubSpot or in place of them.
Lightfield built a cockpit for a founder selling solo. Day AI built the system a revenue team runs on.
Both put agents to work now. Day AI’s are built for the needs of a full revenue team. They stand on one reconciled customer memory, run governed with differing permissions across the team, and deploy to every rep from roles RevOps only needs to build once. Prospecting, prep, follow-ups, and pipeline hygiene, running as your complete customer record or on top of your existing stack. See it run on your own data.
30 minutes. Your data. A product expert, not a pitch.