Lightfield, a buyer relationship administration platform constructed fully round synthetic intelligence, formally launched to the general public this week after a 12 months of quiet growth — a daring pivot by a startup that when had 20 million customers and $43 million within the financial institution constructing one thing utterly totally different.
The San Francisco-based firm is positioning itself as a elementary reimagining of how companies observe and handle buyer relationships, abandoning the guide knowledge entry that has outlined CRMs for many years in favor of a system that routinely captures, organizes, and acts on buyer interactions. With greater than 100 early prospects already utilizing the platform every 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 maybe essentially the most advanced 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 firms have tens of hundreds of thousands of customers, and also you'd be hard-pressed to discover a single one who really loves the product. That drawback is our alternative."
The normal availability announcement marks an uncommon inflection level in enterprise software program: an organization betting that giant language fashions have superior sufficient to interchange structured databases as the muse of business-critical techniques. It's a wager that has attracted backing from Coatue Administration, 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 hundreds of 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 simple 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 wanted 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. Moderately than constructing a horizontal instrument 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 essentially the most logical place to go vertical," Peiris mentioned. The group diminished headcount to a core group of engineers and spent a 12 months constructing in stealth.
Dan Rose, a associate 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 all the way down to a core group of engineers and set to work constructing Lightfield. This was not a simple product to construct, this can be very advanced beneath the hood."
Why Lightfield shops full conversations as an alternative of forcing knowledge into fields
What distinguishes Lightfield from conventional CRMs is architectural, not beauty. Whereas Salesforce, HubSpot, and their opponents 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 entire, unstructured report of what prospects really say and do.
"Conventional CRMs power each interplay via predefined fields — they're compressing wealthy, nuanced buyer conversations into structured database entries," Peiris mentioned. "We retailer buyer knowledge in its uncooked, lossless type. Which means we're capturing considerably extra element and context than a conventional CRM ever might."
In observe, this implies the system routinely data and transcribes gross sales calls, ingests emails, displays product utilization, and maintains what the corporate calls a "relationship timeline" — a whole chronological report of each touchpoint between an organization and its prospects. AI fashions then extract structured info from this uncooked knowledge on demand, permitting firms to reorganize their knowledge mannequin with out guide rework.
"When you understand you want totally different fields or wish to reorganize your schema fully, the system can remap and refill itself routinely," Peiris defined. "You're not locked into choices you made on day one once 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 because the class's inception within the Nineteen Eighties.
Gross sales groups report reviving useless offers and chopping response instances from months to days
Buyer testimonials recommend the automation delivers measurable affect, notably for small groups with out devoted gross sales operations workers. 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 have been revived and have become energetic opps that moved to poc," Postle mentioned. "The issue was, as an alternative of being a instrument of motion and autotracking—HubSpot was a instrument the place I needed to do the work to report buyer convos. Utilizing HubSpot I used to be an information hygienist. Utilizing Lighfield, I’m a better."
Postle reported that his response instances to prospects improved from weeks or months to 1 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 selected function that addresses what he views as the first reason behind misplaced offers: easy neglect. "The killer function is asking 'who haven't 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's prevented not less than 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 distinct period." He mentioned these platforms assume firms have devoted operations groups to configure workflows and keep knowledge high quality — assets most early-stage firms 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 seen as a bellwether for early-stage firm habits — have largely rejected each Salesforce and HubSpot. "When you have 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 simply too costly, too advanced to arrange, and albeit doesn't do sufficient to justify the funding for an early-stage firm."
In response to Peiris, most startups start with spreadsheets and finally graduate to a primary CRM — a transition level the place Lightfield goals to intercede. "More and more, they're selecting Lightfield as an alternative and skipping that intermediate step fully," he mentioned.
This represents a well-known sample in enterprise software program disruption: a brand new technology of firms forming habits round totally different instruments, creating a gap for challengers to ascertain themselves earlier than companies develop giant sufficient to face strain towards industry-standard platforms.
Rose, the Coatue associate, sees Lightfield's technique as intentionally concentrating on this window. "Our technique is to construct shortly and develop alongside our greatest prospects, basically changing into the Salesforce for this new technology of firms," Rose mentioned, paraphrasing the corporate's strategy. "We're there at the start once they're forming their processes, and we scale with them as they develop."
Can Salesforce and HubSpot retrofit their legacy techniques for AI, or is the structure too previous?
Each Salesforce and HubSpot have introduced AI options in latest quarters, including capabilities like dialog intelligence and automatic knowledge entry to their current platforms. The query dealing with Lightfield is whether or not established distributors can incorporate related capabilities—leveraging their current 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 we’ve 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."
Current dialog intelligence instruments like Gong and Income.io, which analyze gross sales calls and supply teaching insights, already serve related capabilities however require Salesforce cases to function. Peiris mentioned Lightfield's benefit comes from unifying your complete knowledge mannequin moderately than layering evaluation on high of fragmented techniques.
"We now have a extra full image of every buyer as a result of we combine firm data, communication sync, product analytics, and full CRM element multi functional place," he mentioned. "That unified context means the work being generated in Lightfield—whether or not it's 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 giant language fashions to extract and interpret info introduces the opportunity of errors—what AI researchers name hallucinations.
Peiris acknowledged each points instantly. 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 Sort I certification and is pursuing each SOC 2 Sort II and HIPAA compliance. "We don't practice fashions on buyer knowledge, interval," Peiris mentioned.
On accuracy, he was equally forthright. "After all it occurs," Peiris mentioned when requested about misinterpretations. "It's inconceivable to utterly get rid of hallucinations when working with giant language fashions."
The corporate's strategy is to require human approval earlier than sending buyer communications or updating essential fields — positioning the system as augmentation moderately than full automation. "We're constructing a instrument that amplifies human judgment, not one which pretends to interchange it fully," Peiris mentioned.
This can be a extra cautious stance than some AI-native software program firms 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 totally different gross sales instruments into one platform
Lightfield's pricing technique displays a broader thesis about enterprise software program economics. Moderately than charging per-seat charges for a degree resolution, the corporate is positioning itself as a consolidated platform that may substitute a number of specialised instruments — gross sales engagement platforms, dialog intelligence techniques, assembly assistants, and the CRM itself.
"The actual drawback is that operating a contemporary go-to-market operate requires cobbling collectively 10 totally different unbiased level options," Peiris mentioned. "Once you pay for 10 separate seat licenses, you're basically paying 10 totally different firms to unravel the identical foundational issues over and over."
The corporate operates primarily via self-service signup moderately than enterprise gross sales groups, which Peiris argues permits for decrease pricing whereas sustaining margins. This can be a widespread playbook amongst fashionable SaaS firms 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 help a sustainable enterprise at scale stays unproven. The corporate's present buyer base skews closely towards early-stage startups—greater than 100 Y Combinator firms, in line with the corporate — a phase with restricted budgets and excessive failure charges.
Rose views this as a deliberate technique moderately than a limitation. "Many startups that survive achieve this as a result of they’ve robust 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 firms in only a few years."
The wager is that Lightfield turns into the system of report for a cohort of fast-growing firms, finally creating an put in base similar to how Salesforce established itself many years 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 check: 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 might permit 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 isn't a moat," Postle mentioned. "HS and Salesforce are going to lose to lightfield as a result of they aren't AI native, irrespective of how a lot they attempt to fake to be."
Rose highlighted an uncommon use case that emerged throughout Lightfield's personal growth: 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's a buyer intelligence layer," Rose mentioned.
This implies potential functions past conventional gross sales workflows, positioning the system as infrastructure for any operate that requires understanding buyer wants—product growth, buyer success, even advertising and marketing technique.
For now, the corporate is concentrated on proving the core worth proposition with early-stage firms. However the broader query Lightfield raises extends past CRM software program particularly: whether or not AI capabilities have superior sufficiently to interchange structured databases as the muse of enterprise techniques, or whether or not the present technology of huge language fashions stays too unreliable for business-critical capabilities.
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 beneficial properties justify the inherent unpredictability of working with techniques that approximate moderately than calculate.
Lightfield is betting that the trade-off has already shifted in favor of approximation, not less than for the hundreds of thousands of salespeople who presently view their CRM as an impediment moderately than an asset. Whether or not that wager proves right will assist outline the following technology of enterprise software program.
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