Lightfield, a buyer relationship administration platform constructed fully round synthetic intelligence, formally launched to the general public this week after a yr of quiet improvement — a daring pivot by a startup that after had 20 million users and $43 million in the bank constructing one thing utterly completely different.
The San Francisco-based firm is positioning itself as a elementary reimagining of how companies monitor and handle buyer relationships, abandoning the handbook knowledge entry that has outlined CRMs for many years in favor of a system that mechanically captures, organizes, and acts on buyer interactions. With greater than 100 early prospects already utilizing the platform day by day — over half spending greater than an hour per day within the system — Lightfield is a direct problem to the legacy enterprise fashions of Salesforce and HubSpot, each of which generate billions in annual income.
“The CRM, categorically, is probably probably the most complicated and lowest satisfaction piece of software program on Earth,” mentioned Keith Peiris, Lightfield’s co-founder and CEO, in an unique interview with VentureBeat. “CRM corporations have tens of thousands and thousands of customers, and you would be hard-pressed to discover a single one who really loves the product. That downside is our alternative.”
The general availability announcement marks an uncommon inflection level in enterprise software program: an organization betting that enormous language fashions have superior sufficient to switch structured databases as the inspiration of business-critical programs. It is a wager that has attracted backing from Coatue Management, which led the corporate’s Sequence A when it was nonetheless constructing presentation software program beneath the identify Tome.
How Tome’s founders deserted 20 million customers to construct a CRM from scratch
The story behind Lightfield’s creation displays each conviction and pragmatism. Tome had achieved important viral success as an AI-powered presentation platform, gaining thousands and thousands of customers who appreciated its visible design and ease of use. However Peiris mentioned the group concluded that constructing lasting differentiation within the general-purpose presentation market would show tough, even with a working product and actual person traction.
“Tome went viral as an AI slides product, and it was visually pleasant and straightforward to make use of—the primary actual generative AI-based presentation platform,” Peiris defined. “However, the extra individuals used it, the extra I noticed that to actually assist individuals talk one thing—something—we would have liked extra context.”
That realization led to a elementary rethinking. The group noticed that the best communication requires deep understanding of relationships, firm dynamics, and ongoing conversations — context that exists most richly in gross sales and customer-facing roles. Fairly than constructing a horizontal device for everybody, they determined to construct vertically for go-to-market groups.
“We selected this lane, ‘gross sales,’ as a result of so many individuals in these roles used Tome, and it appeared like probably the most logical place to go vertical,” Peiris mentioned. The group lowered headcount to a core group of engineers and spent a yr constructing in stealth.
Dan Rose, a companion at Coatue who led the unique funding in Tome, mentioned the pivot validated his conviction within the founding group. “It takes actual guts to pivot, and much more so when the unique product is working,” Rose mentioned. “They shrunk the group right down to a core group of engineers and started working constructing Lightfield. This was not a simple product to construct, this can be very complicated beneath the hood.”
Why Lightfield shops full conversations as a substitute of forcing knowledge into fields
What distinguishes Lightfield from conventional CRMs is architectural, not beauty. Whereas Salesforce, HubSpot, and their rivals require customers to outline inflexible knowledge schemas upfront — dropdown menus, customized fields, checkbox classes — after which manually populate these fields after each interplay, Lightfield shops the whole, unstructured document of what prospects really say and do.
“Conventional CRMs drive each interplay by predefined fields — they’re compressing wealthy, nuanced buyer conversations into structured database entries,” Peiris mentioned. “We retailer buyer knowledge in its uncooked, lossless type. Meaning we’re capturing considerably extra element and context than a standard CRM ever might.”
In follow, this implies the system mechanically information and transcribes gross sales calls, ingests emails, displays product utilization, and maintains what the corporate calls a “relationship timeline” — a whole chronological document of each touchpoint between an organization and its prospects. AI fashions then extract structured data from this uncooked knowledge on demand, permitting corporations to reorganize their knowledge mannequin with out handbook rework.
“In case you understand you want completely different fields or wish to reorganize your schema fully, the system can remap and refill itself mechanically,” Peiris defined. “You are not locked into choices you made on day one whenever you barely understood your gross sales course of.”
The system additionally generates assembly preparation briefs, drafts follow-up emails primarily based on dialog context, and could be queried in pure language — capabilities that symbolize a departure from the passive database mannequin that has outlined CRMs for the reason that class’s inception within the Nineteen Eighties.
Gross sales groups report reviving lifeless offers and reducing response instances from months to days
Buyer testimonials recommend the automation delivers measurable impression, notably for small groups with out devoted gross sales operations employees. Tyler Postle, co-founder of Voker.ai, mentioned Lightfield’s AI agent helped him revive greater than 40 stalled alternatives in a single two-hour session — leads he had uncared for for six months whereas utilizing HubSpot.
“Inside 2 days, 10 of these had been revived and have become lively opps that moved to poc,” Postle mentioned. “The issue was, as a substitute of being a device of motion and autotracking—HubSpot was a device the place I needed to do the work to document buyer convos. Utilizing HubSpot I used to be a knowledge hygienist. Utilizing Lighfield, I’m a better.”
Postle reported that his response instances to prospects improved from weeks or months to at least one or two days, a change noticeable sufficient that prospects commented on it. “Our prospects and prospects have even observed it,” he mentioned.
Radu Spineanu, co-founder of Humble Ops, highlighted a particular function that addresses what he views as the first explanation for misplaced offers: easy neglect. “The killer function is asking ‘who have not I adopted up with?'” Spineanu mentioned. “Most offers die from neglect, not rejection. Lightfield catches these dropped threads and might draft and ship the follow-up instantly. That is prevented a minimum of three offers from going chilly this quarter.”
Spineanu had evaluated competing fashionable CRMs together with Attio and Clay earlier than choosing Lightfield, dismissing Salesforce and HubSpot as “constructed for a unique period.” He mentioned these platforms assume corporations have devoted operations groups to configure workflows and preserve knowledge high quality — sources most early-stage corporations lack.
Why Y Combinator startups are rejecting Salesforce and beginning with AI-native instruments
Peiris claims that the present batch of Y Combinator startups — extensively considered as a bellwether for early-stage firm habits — have largely rejected each Salesforce and HubSpot. “In case you had been to ballot a random sampling of present YC startups and ask whether or not they’re utilizing Salesforce or HubSpot, the overwhelming reply could be ‘no,'” he mentioned. “Salesforce is just too costly, too complicated to arrange, and albeit does not do sufficient to justify the funding for an early-stage firm.”
In response to Peiris, most startups start with spreadsheets and ultimately graduate to a primary CRM — a transition level the place Lightfield goals to intercede. “More and more, they’re selecting Lightfield as a substitute and skipping that intermediate step fully,” he mentioned.
This represents a well-recognized sample in enterprise software program disruption: a brand new era of corporations forming habits round completely different instruments, creating a gap for challengers to determine themselves earlier than companies develop massive sufficient to face stress towards industry-standard platforms.
Rose, the Coatue companion, sees Lightfield’s technique as intentionally concentrating on this window. “Our technique is to construct shortly and develop alongside our greatest prospects, primarily turning into the Salesforce for this new era of corporations,” Rose mentioned, paraphrasing the corporate’s strategy. “We’re there at first after they’re forming their processes, and we scale with them as they develop.”
Can Salesforce and HubSpot retrofit their legacy programs for AI, or is the structure too outdated?
Each Salesforce and HubSpot have introduced AI options in latest quarters, including capabilities like dialog intelligence and automatic knowledge entry to their present platforms. The query dealing with Lightfield is whether or not established distributors can incorporate comparable capabilities—leveraging their present buyer bases and integrations — or whether or not elementary architectural variations create a real moat.
Peiris argues the latter. “The elemental distinction is in how we retailer knowledge,” he mentioned. “As a result of now we have entry to that full context, the evaluation we offer and the work we generate tends to be considerably larger high quality than instruments constructed on high of conventional database buildings.”
Present dialog intelligence instruments like Gong and Revenue.io, which analyze gross sales calls and supply teaching insights, already serve comparable features however require Salesforce cases to function. Peiris mentioned Lightfield’s benefit comes from unifying all the knowledge mannequin moderately than layering evaluation on high of fragmented programs.
“We now have a extra full image of every buyer as a result of we combine firm information, communication sync, product analytics, and full CRM element multi function place,” he mentioned. “That unified context means the work being generated in Lightfield—whether or not it is evaluation, follow-ups, or insights—tends to be considerably larger high quality.”
The privateness and accuracy considerations that include AI-automated buyer interactions
The structure creates apparent dangers. Storing full dialog histories raises privateness considerations, and counting on massive language fashions to extract and interpret data introduces the opportunity of errors—what AI researchers name hallucinations.
Peiris acknowledged each points immediately. On privateness, the corporate maintains that decision recording follows commonplace practices, with seen notifications that recording is in progress, and that storing gross sales correspondence mirrors what CRM distributors have finished for many years. The corporate has achieved SOC 2 Kind I certification and is pursuing each SOC 2 Kind II and HIPAA compliance. “We do not practice fashions on buyer knowledge, interval,” Peiris mentioned.
On accuracy, he was equally forthright. “In fact it occurs,” Peiris mentioned when requested about misinterpretations. “It is not possible to utterly remove hallucinations when working with massive language fashions.”
The corporate’s strategy is to require human approval earlier than sending buyer communications or updating important fields — positioning the system as augmentation moderately than full automation. “We’re constructing a device that amplifies human judgment, not one which pretends to switch it fully,” Peiris mentioned.
It is a extra cautious stance than some AI-native software program corporations have taken, reflecting each technical realism about present mannequin capabilities and potential legal responsibility considerations round customer-facing errors.
How Lightfield plans to consolidate ten completely different gross sales instruments into one platform
Lightfield’s pricing technique displays a broader thesis about enterprise software program economics. Fairly than charging per-seat charges for a degree resolution, the corporate is positioning itself as a consolidated platform that may change a number of specialised instruments — gross sales engagement platforms, dialog intelligence programs, assembly assistants, and the CRM itself.
“The actual downside is that working a contemporary go-to-market perform requires cobbling collectively 10 completely different unbiased level options,” Peiris mentioned. “Whenever you pay for 10 separate seat licenses, you are primarily paying 10 completely different corporations to unravel the identical foundational issues time and again.”
The corporate operates primarily by self-service signup moderately than enterprise gross sales groups, which Peiris argues permits for decrease pricing whereas sustaining margins. It is a widespread playbook amongst fashionable SaaS corporations however represents a elementary distinction from Salesforce’s mannequin, which depends closely on direct gross sales and buyer success groups.
Whether or not this strategy can assist a sustainable enterprise at scale stays unproven. The corporate’s present buyer base skews closely towards early-stage startups—greater than 100 Y Combinator corporations, in line with the corporate — a section with restricted budgets and excessive failure charges.
Rose views this as a deliberate technique moderately than a limitation. “Many startups that survive accomplish that as a result of they’ve sturdy fundamentals,” he mentioned, explaining the corporate’s thesis. “The truth is that many startups scale terribly quick — they go from 10 individuals to enterprise-sized corporations in only a few years.”
The wager is that Lightfield turns into the system of document for a cohort of fast-growing corporations, ultimately creating an put in base similar to how Salesforce established itself a long time in the past. Whether or not AI capabilities alone present adequate differentiation to execute that technique—or whether or not incumbents can adapt shortly sufficient to defend their positions—will probably decide the corporate’s trajectory.
The actual take a look at: whether or not gross sales groups will belief AI sufficient to let it run their enterprise
The corporate has outlined a number of areas for growth, together with an open platform for workflows and webhooks that will enable third-party integrations. Early prospects have particularly requested connections with instruments like Apollo for prospecting and Slack for group communication — gaps that Postle, the Voker.ai founder, acknowledged however dismissed as non permanent.
“The truth that HS and Salesforce have these integrations already is not a moat,” Postle mentioned. “HS and Salesforce are going to lose to lightfield as a result of they are not AI native, irrespective of how a lot they attempt to faux to be.”
Rose highlighted an uncommon use case that emerged throughout Lightfield’s personal improvement: the corporate’s product group used the CRM itself to investigate buyer conversations and establish function requests. “On this sense, Lightfield greater than only a gross sales database, it is a buyer intelligence layer,” Rose mentioned.
This implies potential purposes past conventional gross sales workflows, positioning the system as infrastructure for any perform that requires understanding buyer wants—product improvement, buyer success, even advertising and marketing technique.
For now, the corporate is concentrated on proving the core worth proposition with early-stage corporations. However the broader query Lightfield raises extends past CRM software program particularly: whether or not AI capabilities have superior sufficiently to switch structured databases as the inspiration of enterprise programs, or whether or not the present era of huge language fashions stays too unreliable for business-critical features.
The reply will probably emerge not from technical benchmarks however from buyer habits—whether or not gross sales groups really belief AI-generated insights sufficient to base choices on them, and whether or not the effectivity features justify the inherent unpredictability of working with programs that approximate moderately than calculate.
Lightfield is betting that the trade-off has already shifted in favor of approximation, a minimum of for the thousands and thousands of salespeople who at the moment view their CRM as an impediment moderately than an asset. Whether or not that wager proves appropriate will assist outline the following era of enterprise software program.
