Lightfield, a buyer relationship administration platform constructed totally round synthetic intelligence, formally launched to the general public this week after a yr of quiet improvement — a daring pivot by a startup that when had 20 million customers and $43 million within the financial institution constructing one thing fully totally different.
The San Francisco-based firm is positioning itself as a basic reimagining of how companies monitor and handle buyer relationships, abandoning the guide knowledge entry that has outlined CRMs for many years in favor of a system that robotically captures, organizes, and acts on buyer interactions. With greater than 100 early clients 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 probably probably 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 thousands and 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 basic 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 methods. 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 below the title 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 crew concluded that constructing lasting differentiation within the general-purpose presentation market would show troublesome, 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 essentially assist individuals talk one thing—something—we would have liked extra context."
That realization led to a basic rethinking. The crew noticed that the simplest communication requires deep understanding of relationships, firm dynamics, and ongoing conversations — context that exists most richly in gross sales and customer-facing roles. Somewhat 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 crew diminished 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 crew. "It takes actual guts to pivot, and much more so when the unique product is working," Rose mentioned. "They shrunk the crew right down to a core group of engineers and started working constructing Lightfield. This was not a straightforward product to construct, this can be very advanced below 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 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 file of what clients 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 kind. Meaning we're capturing considerably extra element and context than a standard CRM ever might."
In observe, this implies the system robotically data and transcribes gross sales calls, ingests emails, displays product utilization, and maintains what the corporate calls a "relationship timeline" — an entire chronological file of each touchpoint between an organization and its clients. AI fashions then extract structured data from this uncooked knowledge on demand, permitting firms to reorganize their knowledge mannequin with out guide rework.
"In the event you notice you want totally different fields or wish to reorganize your schema totally, the system can remap and refill itself robotically," Peiris defined. "You're not locked into choices you made on day one while you barely understood your gross sales course of."
The system additionally generates assembly preparation briefs, drafts follow-up emails based mostly on dialog context, and might be queried in pure language — capabilities that characterize 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 chopping response instances from months to days
Buyer testimonials counsel 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 a substitute of being a device of motion and autotracking—HubSpot was a device the place I needed to do the work to file buyer convos. Utilizing HubSpot I used to be an information hygienist. Utilizing Lighfield, I’m a more in-depth."
Postle reported that his response instances to prospects improved from weeks or months to 1 or two days, a change noticeable sufficient that clients commented on it. "Our prospects and clients have even seen it," he mentioned.
Radu Spineanu, co-founder of Humble Ops, highlighted a selected function that addresses what he views as the first reason for 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 no 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 unique period." He mentioned these platforms assume firms have devoted operations groups to configure workflows and keep knowledge high quality — sources 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 conduct — have largely rejected each Salesforce and HubSpot. "In the event 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 can be 'no,'" he mentioned. "Salesforce is just too costly, too advanced to arrange, and admittedly 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 a substitute and skipping that intermediate step totally," he mentioned.
This represents a well-recognized 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 stress towards industry-standard platforms.
Rose, the Coatue companion, sees Lightfield's technique as intentionally focusing on this window. "Our technique is to construct rapidly and develop alongside our greatest clients, basically changing into the Salesforce for this new technology of firms," Rose mentioned, paraphrasing the corporate's method. "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 methods 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 current platforms. The query dealing with Lightfield is whether or not established distributors can incorporate comparable capabilities—leveraging their current buyer bases and integrations — or whether or not basic 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 now have entry to that full context, the evaluation we offer and the work we generate tends to be considerably greater high quality than instruments constructed on high of conventional database constructions."
Present dialog intelligence instruments like Gong and Income.io, which analyze gross sales calls and supply teaching insights, already serve comparable capabilities however require Salesforce situations to function. Peiris mentioned Lightfield's benefit comes from unifying the complete knowledge mannequin moderately than layering evaluation on high of fragmented methods.
"We’ve 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's evaluation, follow-ups, or insights—tends to be considerably greater high quality."
The privateness and accuracy issues that include AI-automated buyer interactions
The structure creates apparent dangers. Storing full dialog histories raises privateness issues, and counting on giant language fashions to extract and interpret data introduces the potential for errors—what AI researchers name hallucinations.
Peiris acknowledged each points instantly. On privateness, the corporate maintains that decision recording follows normal practices, with seen notifications that recording is in progress, and that storing gross sales correspondence mirrors what CRM distributors have performed for many years. The corporate has achieved SOC 2 Kind I certification and is pursuing each SOC 2 Kind II and HIPAA compliance. "We don't 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's unattainable to fully remove hallucinations when working with giant language fashions."
The corporate's method is to require human approval earlier than sending buyer communications or updating vital fields — positioning the system as augmentation moderately than full automation. "We're constructing a device that amplifies human judgment, not one which pretends to interchange it totally," 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 issues 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. Somewhat than charging per-seat charges for a degree resolution, the corporate is positioning itself as a consolidated platform that may exchange a number of specialised instruments — gross sales engagement platforms, dialog intelligence methods, assembly assistants, and the CRM itself.
"The true drawback is that working a contemporary go-to-market perform requires cobbling collectively 10 totally different unbiased level options," Peiris mentioned. "While you pay for 10 separate seat licenses, you're basically paying 10 totally different firms to resolve the identical foundational issues again 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. This can be a frequent playbook amongst fashionable SaaS firms however represents a basic distinction from Salesforce's mannequin, which depends closely on direct gross sales and buyer success groups.
Whether or not this method 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 firms, in keeping 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 fact is that many startups scale terribly quick — they go from 10 individuals to enterprise-sized firms in just some years."
The guess is that Lightfield turns into the system of file for a cohort of fast-growing firms, finally creating an put in base akin to how Salesforce established itself a long time in the past. Whether or not AI capabilities alone present enough differentiation to execute that technique—or whether or not incumbents can adapt rapidly sufficient to defend their positions—will possible decide the corporate's trajectory.
The true 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 may enable third-party integrations. Early clients have particularly requested connections with instruments like Apollo for prospecting and Slack for crew communication — gaps that Postle, the Voker.ai founder, acknowledged however dismissed as short-term.
"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, regardless of how a lot they attempt to fake to be."
Rose highlighted an uncommon use case that emerged throughout Lightfield's personal improvement: the corporate's product crew used the CRM itself to investigate buyer conversations and determine function requests. "On this sense, Lightfield greater than only a gross sales database, it's 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 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 methods, or whether or not the present technology of huge language fashions stays too unreliable for business-critical capabilities.
The reply will possible emerge not from technical benchmarks however from buyer conduct—whether or not gross sales groups really belief AI-generated insights sufficient to base choices on them, and whether or not the effectivity positive aspects justify the inherent unpredictability of working with methods that approximate moderately than calculate.
Lightfield is betting that the trade-off has already shifted in favor of approximation, no less than for the thousands and thousands of salespeople who at present view their CRM as an impediment moderately than an asset. Whether or not that guess proves right will assist outline the following technology of enterprise software program.
