AI built for the way consumers buy. Which is never a straight line.

The new-age consumer browses at midnight, ghosts your call, and texts back days later. Our AI has seen every turn, across the journeys of 1,600+ consumer businesses.

Book a demo See how it works

Scroll

One consumer journey.

10 touchpoints5 channels3 weeks9 leaks

Social: Clicks an ad. A scroll, a tap. Interest starts in someone else’s feed. Where it leaks: Some tap the ad and bounce before the page loads.
11:40 pm: Browses your site. 11:40 PM. They read everything. Nobody is there to answer. Where it leaks: Late-night browsers leave when nobody answers.
Web chat: Asks the chatbot. A real question, asked in their own words. Where it leaks: A slow or canned answer sends them back to search.
Day 2: Compares 4 options. You’re one of four tabs. The others are a tap away. Where it leaks: Three other options are one tap away.
Phone: Misses your call. You call back the next day. They’re in a meeting. Where it leaks: A missed call with no follow-up goes cold.
9 days: Goes quiet. Nine days of nothing. This is where journeys quietly end. Where it leaks: Nine quiet days. This is where journeys end.
Day 11: Replies by text. Day 11. They’re back, on their own terms. Where it leaks: A reply that waits until morning gets ignored.
Email: Sends documents. Three files, three reminders, one complete record. Where it leaks: One missing document stalls the whole file.
Day 17: Books a visit. A slot on the calendar. Now don’t lose them before it. Where it leaks: Booked visits still no-show without a nudge.
Day 21: Says yes. Day 21. Ten touchpoints, five channels, one decision.

SocialClicks an ad
11:40 pmBrowses your site
Web chatAsks the chatbot
Day 2Compares 4 options
PhoneMisses your call
9 daysGoes quiet
Day 11Replies by text
EmailSends documents
Day 17Books a visit
Day 21Says yes

Nine places to lose them.

Why our AI works

AI gets things done when it has context. Without it, it’s guessing.

Knowing who is ready, what is missing and what to do next takes context, and that comes from running consumer journeys at scale.

Millionsof journeys run end to end, from first inquiry to renewal

400M+interactions a month across calls, chats and email

1,600+consumer businesses,
from growing teams to large enterprises

Vertical depth

We’re built for high-velocity consumer funnels, with the stages, documents, and deadlines already in place.

The whole journey

We cover the whole journey on one platform, from first inquiry to retention, with every handoff on one record.

A partner that stays

Our AI Lab squad works on your funnel with you, and stays until the results show.

95% of AI pilots show no P&L impact

Context is half the story. The other half is action.

Most AI stops at insight. LeadSquared AI sees every step of the journey and acts on it, from one record.

Context What it knows. The full picture of every buyer, on one record.

Leads and sources Web activity and forms Journey stage Every conversation

Every move lands.Because it knows before it acts.

Action What it does. The next move, made by your team or by AI.

Automation Campaigns Calls, human or AI Text and email Tasks

How we close the gap

One AI suite that sees and acts. Across the whole consumer journey.

Lumen runs across everything. Augmented AI and Agentic AI work on one system of record, and our Co-innovation Lab builds what’s missing. Pick any product to see what it does.

Lumen: The AI layer across the suite. You ask in plain English, Lumen answers and acts. Copilot, always on: Ask about your data, build reports and complete tasks within your permissions. MCP: Connects LeadSquared to the AI tools your team already uses. Agent Studio: Build your own agents in plain English.
Propensity scoring: Every inquiry arrives scored, with the reason shown. Ranks every inquiry by how likely they are to commit, from their forms, calls, chats and web visits.
Next-best action: The next step for every record, inside the screen your team already uses. Suggests the next call, message or task for each person. It suggests; your team decides.
NoteSpark + Call IQ: Call notes, objections and coaching, written for you. Summarizes every call, catches goals and objections, and logs the next step to the record with no typing.
Smart Field Assist: Record fields filled in for your team. Fills in record fields as information arrives from calls, chats and forms.
AI reporting + SIERA: Ask a question, get the report. Answers reporting questions in plain English and builds the report or chart for you.
Flash: Reaches the ready ones first. Scores and routes every new inquiry the moment it lands, so the right person calls the people most ready to act.
Sherlock: Checks each file before a person opens it. Finds what is missing or wrong in documents and forms and asks for it the same day, so people review only the exceptions.
Nova: Spots likely no-shows and refills the slot. Predicts who may miss a visit or appointment, nudges them the day before and offers freed slots to the waitlist.
Hawke: Warns leadership when numbers start to slip. Watches the journey against normal every night and flags a slip to leadership before it shows in the results.
RevGuard: Flags who is about to drop out or stop coming. Spots people who are disengaging and hands your team a ready outreach while they can still be kept.
Invorto: Voice AI that calls every new inquiry, qualifies and books. Answers and calls back around the clock in multiple languages, qualifies, books the next step and hands over with the full conversation.
LeadEdge AI Lab: Our AI engineers embed with your team. We start where your journey loses the most people, build the agent with your team and test it on your live data.
Outcome contract: Named goals, targets and owners, agreed before you buy. Each agent comes with the number it must move, the target, who owns it and how it is measured on your live data.
Born in the Lab: Every standard agent started as a build with one customer. Co-build on your journey, prove the number on live data, then ship what works to every team.
Agent Studio: Or build agents yourself. Pick the trigger, set the rules, choose the action and switch it on. Your team shapes agents around its own processes, then extends them to the teams that need them.

One system of recordB2C journeys

AI-ready dataData sync · connectors · partner signals

GovernanceRole-based access · consent tracking · audit trail

SecurityRegional hosting · data masking · human oversight

LiveIn the LabComing soon

1Augmented AI

AI does the legwork. Your team has the final say.

It scores inquiries, writes call notes, and builds reports inside the tools your team already uses, so everyone gets more done in a day.

The rule

Same team, same day. Just faster.

Works where you already work. On the screens, calls and reports your team already uses.
Never overrides. Every suggestion shows its reason, and your team can always say no.

Advisor's screen · student record patient record

Maya R.MSc Data Science · Fall intake · inquiry 9:47 pm

Marcus T.New patient · knee pain · called 7:02 pm

Likely to enroll book

Next best action

Call now — she opened the tuition page twice in 20 minutesCall now — he checked insurance coverage twice tonight

AssignedTo Priya, who converts MSc inquiries best To Dana, the coordinator for new orthopedic patients

Why this score

9:47 pmInquiry form · MSc Data Science+18

9:52 pmTuition page · viewed twice+24

10:05 pmAsked chatbot about housing+11

—Similar profiles enroll at 3× the average+29

7:02 pmCalled · knee pain, wants first visit+22

7:10 pmInsurance coverage page · viewed twice+20

7:14 pmChecked open slots this week+15

—Similar patients book within 48 hours+25

2Agentic AI

Agents that never clock out. Your team steps in where it matters.

Each one handles a single job around the clock and hands over when judgment is needed. Pick one to see it work.

Book a demo

Operator

Invorto

Calls every new inquiry, qualifies and books.

Live

Marcus T…Jordan LeeSam PatelRiley Chen

LumenJD

Invorto - Voice AI

InvortoVoice AI agent

StatusLive nowListen in

38 new inquiries called tonight. 14 booked a first visit before morning.

Every new inquiry gets a call within a minute, around the clock and in multiple languages. Qualified callers are booked and handed over with the full conversation.

Live call · 9:48 pm00:41

InvortoMarcus T.

Invorto

Hi Marcus, I can get you seen this week. Is Thursday good?

Marcus

Thursday morning works.

Invorto

Booked, 10 am. I'll text the intake forms.

✓ Booked · logged to the record

QualificationCaptured on the call, written to the record

Reason: Knee pain, wants a first visit
Insurance: PPO · coverage checked
Preferred time: Thursday morning
Language: English
Outcome: Booked · Thu 10 am
Handed to: Dana, new-patient coordinator

Calls placed38since 6 pm

First contact42smedian, day or night

Qualified21ready for a person

Booked14on the calendar

Languages4spoken tonight

Maya R…Alex KimSam PatelRiley Chen

LumenJD

Invorto - Voice AI

InvortoVoice AI agent

StatusLive nowListen in

52 new inquiries called tonight. 18 booked an advisor call before morning.

Every new inquiry gets a call within a minute, around the clock and in multiple languages. Qualified students are booked and handed over with the full conversation.

Live call · 9:48 pm00:41

InvortoMaya R.

Invorto

Hi Maya, thanks for asking about the MSc. Got two minutes?

Maya

Sure — is there a fall start?

Invorto

Yes. I'll book you with an advisor at 10 tomorrow.

✓ Booked · logged to the record

QualificationCaptured on the call, written to the record

Program: MSc Data Science
Intake: Fall 2026
Budget: Scholarship covers it
Language: English
Outcome: Booked · advisor, 10 am
Handed to: Priya, best on MSc inquiries

Calls placed52since 6 pm

First contact42smedian, day or night

Qualified30ready for a person

Booked18on the calendar

Languages5spoken tonight

Live call · 9:48 pm00:41

Invorto

Hi Maya, thanks for asking about the MSc. Got two minutes?

Hi Marcus, I can get you seen this week. Is Thursday good?

Maya Marcus

Sure — is there a fall start?

Thursday morning works.

Invorto

Yes. I'll book you with an advisor at 10 tomorrow.

Booked, 10 am. I'll text the intake forms.

✓ Booked · logged to the record

The number it ownsEvery call answered, 24/7, multiple languages

Visit invorto.ai

Concierge

Flash

Reaches the ready ones first.

In the Lab

Marcus T…×Jordan LeeSam Patel

LumenJD

Activity HistoryPatient DetailsOpportunitiesTasksDocumentsMember of ListsAudit TrailAgent Audit Trail

Flash60 seconds to scheduleDecided 16 Sept 2026, 22:08

Active

Re-inquiry — came back on their own after an earlier visit request. Reach out today

70/100

Visit readiness bucketHigh

Hide score

Detected intent: Exploring
Intent confidence: 60%
Service interest: Orthopedics
Service line fit: Fit
Inquiry urgency: Urgent
Referral source score: 90
Distance to clinic: 11 mi
ZIP: 98124

AI reasoning

Marcus has a recent ankle injury with pain, which fits Orthopedics well and shows high readiness to schedule, but the acute injury nature warrants a prompt follow-up rather than standard routine pacing. Staff should reach out within a day or two to schedule an orthopedic evaluation, noting he is self-pay and came via patient referral.

Maya R…×Alex KimSam Patel

LumenJD

Activity HistoryStudent DetailsApplicationsTasksDocumentsMember of ListsAudit TrailAgent Audit Trail

Flash42 seconds to first contactDecided 16 Sept 2026, 21:48

Active

Ready to enroll — opened the tuition page twice in 20 minutes. Call now

82/100

Enrollment readiness bucketHigh

Hide score

Detected intent: Applying
Intent confidence: 74%
Program interest: MSc Data Science
Program fit: Fit
Inquiry urgency: Urgent
Source score: 88
Intake: Fall 2026
Routed to: Priya, best on MSc inquiries

AI reasoning

Maya inquired about the MSc Data Science at 9:47 pm, viewed tuition twice and asked the chatbot about housing, so readiness is high for the fall intake. Similar profiles enroll at 3× the average. Priya should call now, confirm the scholarship covers the budget and send the housing guide with a campus visit slot.

9:47 pmNew inquiry · MSc Data Science knee pain, first visitReady · 82

9:47 pmRouted to Priya, best on MSc inquiries Dana, new-patient coordinatorRouted

9:48 pmFirst contact made0:42

42 secfrom inquiry to first contact, at night, with no one on shift

The number it ownsFirst contact in under 60 seconds

Inspector

Sherlock

Checks each application intake file before a person opens it.

In the Lab

Marcus T…×Jordan LeeSam Patel

LumenJD

Activity HistoryPatient DetailsOpportunitiesTasksDocumentsMember of ListsAudit TrailAgent Audit Trail

SherlockIntake QA review

Active

Needs reviewMinor gapsConfidence: Low

Summary

Government ID and insurance card were not usable for verification; other insurance and consent details on the form appear complete and consistent.

Concerns

Government ID upload (mx_Custom_5) appears to be a generic logo image, not a legible identity document, so name and date of birth could not be verified
Insurance Card, Signed Consent Forms, Prior Medical Records, Immunization Record, and Lab or Imaging Results were not uploaded
Service line plausibility (Orthopaedics for ankle pain) looks consistent based on symptoms alone, but no supporting records were available to confirm

Advisory notes

Reviewer should request a clear, legible government ID photo and insurance card to complete identity and insurance verification before scheduling.

Maya R…×Alex KimSam Patel

LumenJD

Activity HistoryStudent DetailsApplicationsTasksDocumentsMember of ListsAudit TrailAgent Audit Trail

SherlockApplication QA review

Active

Needs review1 document missingConfidence: High

Summary

4 documents received. Transcript grades and dates match the application and the ID matches the record; the recommendation letter has not been uploaded yet.

Checks

Transcript: courses, grades and dates match the application form
ID: name and date of birth match the student record
Recommendation letter: missing, so the application cannot move to committee review

Action taken

Request sent to Maya with a one-tap upload link. The counselor will open a complete file once the letter arrives. File checked in 24 seconds.

Application · Maya R. Intake file · Marcus T.4 documents received

✓Transcript · grades and dates match Referral · diagnosis and doctor match

✓ID · name matches the record Insurance card · plan is active

!Recommendation letter · missing Prior authorization · needed

Request sent to Maya with a one-tap upload link Request sent to the referring office

24 secto check the whole file, before a person opens it

The number it ownsEvery file checked in under 30 seconds

Scheduler

Nova

Spots likely no-shows and refills the slot.

In the Lab

Marcus T…Jordan LeeSam PatelRiley Chen

LumenJD

Nova Console

Nova ConsoleNo-show prediction

Last scanOct 14, 12:07 AMRun risk scoring

31 appointments are likely to no-show. 14 are high-risk before the next visit.

Scored across 500 upcoming appointments and 7 service lines, ranked by risk and how soon the appointment falls.

OverviewAt-risk patientsOpen slotsWaitlistInterventions

Patients scanned500upcoming appointments

High risk316.2% of the book

Medium92monitor

Low21stable

Open slots70ready to fill

Waitlist50patients waiting

Executive insightWritten by Nova over the computed figuresRegenerate

Today's book carries 31 high-risk appointments out of 500 upcoming, a 6.2% no-show rate. Risk concentrates in ABA Therapy (6 high-risk of 65), where evening slots and prior no-shows cluster. Cascade is the most exposed clinic. Work the high-risk queue first — the 14 appointments landing soonest have the least time for outreach to land. 50 waitlist patients are ready to backfill any slot that frees up.

Risk distribution144 scored · 356 not yet scored

High risk 31

High
Medium
Low

Maya R…Alex KimSam PatelRiley Chen

LumenJD

Nova Console

Nova ConsoleVisit no-show prediction

Last scanOct 14, 12:07 AMRun risk scoring

26 campus visits are likely to no-show. 9 are high-risk before Thursday.

Scored across 320 upcoming campus visits and advising sessions in 6 programs, ranked by risk and how soon the visit falls.

OverviewAt-risk studentsOpen slotsWaitlistInterventions

Visits scanned320upcoming visits

High risk268.1% of the calendar

Medium58monitor

Low236stable

Open slots41ready to fill

Waitlist35students waiting

Executive insightWritten by Nova over the computed figuresRegenerate

This week carries 26 high-risk visits out of 320, an 8.1% no-show rate. Risk concentrates in MSc Data Science (7 high-risk of 48), where evening inquiries rarely confirm. Reminders go out at the time each student usually replies, with an easy reschedule link. If there is no reply by 6 pm, the slot is offered to the 35 students on the waitlist.

Risk distribution320 scored · next 7 days

High risk 26

High
Medium
Low

Thu 10:00Campus visit · Maya R. First visit · Marcus T.

No-show risk 74%

✓Reminder sent at the time they usually reply

✓Easy reschedule link included

…No reply by 6 pm: slot offered to the waitlist

Slot filledthe visit still happens, with someone who can make it

The number it ownsEvery empty slot refilled from the waitlist

Guardian

RevGuard

Flags who is about to drop out stop coming.

In the Lab

Marcus T…Jordan LeeSam PatelRiley Chen

LumenJD

RevGuard - HC

RevGuardRevenue protection

Last scanOct 14, 12:06 AMRun risk scoring

OverviewImpactTrendsHow it learns

$273,427 of revenue is at risk across the open book.

$195,797 sits in episodes patients are likely to drop, $77,630 in balances unlikely to be collected. 33 cases are critical.

Total revenue at risk$273,427risk-adjusted, both engines

Episode protection$195,797104 open episodes

Financial recovery$77,630111 open balances

Patients flagged215across the queue

Critical33≥ $2,500 at risk

High48$1,000 to $2,499

Executive readWritten by RevGuard over the computed figures

Total revenue at risk stands at $273,427, with episode protection accounting for $195,797 and financial recovery making up the remaining $77,630. The largest single exposure is Taylor Reed at $9,274, driven by a $9,648 self-pay balance aged 175 days. With 33 critical and 48 high cases overall, act first on Taylor Reed's aged balance and the coverage lapses behind Alex Morgan and Jamie Brooks to stop further episode leakage.

Where the money sitsTwo engines, one prioritized list

Episode protection$195,797104 open episodes

Alex MorganABA Therapy · Insured$7,310
Jamie BrooksABA Therapy · Insured$7,306
Riley CarterABA Therapy · Insured$7,038

Financial recovery$77,630111 open balances

Taylor ReedUninsured · Self-pay$9,274
Casey NguyenUninsured · Self-pay$4,213
Morgan DiazMedicaid · Insured$3,799

Maya R…Alex KimSam PatelRiley Chen

LumenJD

RevGuard - Education

RevGuardRevenue protection

Last scanOct 14, 12:06 AMRun risk scoring

OverviewImpactTrendsHow it learns

$1,184,000 of tuition is at risk across the student book.

$742,000 sits with admitted students likely to melt before term, $442,000 with enrolled students likely to leave in the next 30 days. 41 cases are critical.

Total tuition at risk$1,184,000risk-adjusted, both engines

Summer melt$742,00058 admitted students

Retention$442,00039 enrolled students

Students flagged97across the queue

Critical41≥ $10,000 at risk

High33$5,000 to $9,999

Executive readWritten by RevGuard over the computed figures

Tuition at risk stands at $1,184,000, with summer melt accounting for $742,000 and retention for $442,000. Melt concentrates in admitted MSc students who deposited but have not registered for orientation. Retention risk shows up as falling portal logins and late assignments. Outreach is drafted for each student's advisor, with the reason attached, while there is still time to keep them.

Where the money sitsTwo engines, one prioritized list

Summer melt$742,00058 admitted students

Student A. KimMSc Data Science · Deposited$18,400
Student J. ParkMBA · Deposited$16,900
Student R. SilvaBSc Nursing · Admitted$14,200

Retention$442,00039 enrolled students

Student T. AhmedYear 2 · Portal logins down 60%$12,600
Student L. MorenoYear 1 · Two assignments late$11,800
Student C. ItoYear 3 · Stopped opening email$9,400

SignalPortal logins down 60% in 3 weeks Missed two follow-up visits

SignalTwo assignments late Stopped opening reminders

RiskLikely to leave in the next 30 daysHigh

Outreach drafted for the student’s advisor the care team, with the reason attached

Caught earlywhile there’s still time to keep them

The number it ownsRevenue at risk, priced in dollars

Watchdog

Hawke

Warns leadership when numbers start to slip.

In the Lab

Marcus T…Jordan LeeSam PatelRiley Chen

LumenJD

Agent Hawke - Healthcare

Agent HawkeAnomaly intelligence

Last scan14/10/2026, 00:07:04Re-scan

156 flags across the book. 14 need attention before the next visit.

Detected across 353 patients and 10 detectors, ranked by severity, corroboration and how soon the appointment falls.

Patients scanned353joined across sources

Flags15610 detectors

Critical14act before the visit

High87this week

Medium55monitor

Executive insightWritten by Hawke over the detected flags

Current book shows 156 total flags, with 14 critical and 87 high severity, so the risk load is concentrated in operational and compliance gaps rather than scattered evenly. The sharpest concentration is in coverage lapses (34, all high severity) and waitlist backfill gaps (25), alongside a cluster of unresolved claim denials (17) with no rework logged. Patient J. Lee stands out as a single patient carrying multiple critical and high flags at once, making him the top priority for same-day review.

By type

Unfulfilled order19
Waitlist backfill gap11
Service-line no-show pattern10
No-show stacking9
Intake documentation gap3
Referral cooling (contact)3

Maya R…Alex KimSam PatelRiley Chen

LumenJD

Agent Hawke - Education

Agent HawkeAnomaly intelligence

Last scan14/10/2026, 00:07:04Re-scan

112 flags across the cycle. 11 need attention before the deposit deadline.

Detected across 1,240 applicants and 10 detectors, ranked by severity, corroboration and how soon the deadline falls.

Applicants scanned1,240joined across sources

Flags11210 detectors

Critical11act before the deadline

High58this week

Medium43monitor

Executive insightWritten by Hawke over the detected flags

This cycle shows 112 flags, with 11 critical and 58 high severity. The sharpest signal is paid search applications down 18% vs plan, three weeks before it would have shown up in the month-end report. Stalled applications and missing transcripts cluster in MSc programs, and counselor follow-up gaps are widest on inquiries that arrive after 9 pm. Flagged to leadership, with the likely cause.

By type

Paid search below plan24
Application stalled19
Missing transcript16
Counselor follow-up gap12
Event no-show pattern9
Scholarship document gap6

Applications vs plan Booked visits vs plan

Paid search applications down 18% vs plan Referral bookings down 14% vs planFlagged to leadership, with the likely cause

3 weeksbefore it would have shown up in the month-end report

The number it ownsProblems flagged 2–3 weeks early

Analyst

Quill

Answers any reporting question.

In the Lab

Marcus T…Jordan LeeSam PatelRiley Chen

LumenJD

Quill - Healthcare

75 upcoming appointments are High no-show riskNova risk band, act before the visitInvestigate

Ask Quill about patients, referrals, scheduling, intake, coverage, or revenueGenerate

Inquiry → booked → seen, by sourceReferral conversion & leakage by organizationNo-show rate by service lineIntake readiness

What would you like to know?

Ask Quill any question about your patients, referrals, scheduling, intake, coverage, or revenue. Every report is computed live from your CRM and Mavis data.

Every figure is computed deterministically and shows the data slice behind it. Quill reports historical actuals and surfaces other agents' outputs (Nova, Flash, Sherlock) with attribution; it never predicts. Demo or synthetic values are labelled as such.

Maya R…Alex KimSam PatelRiley Chen

LumenJD

Quill - Education

142 deposits this week, up 9%Most of the rise came from referralsInvestigate

Ask Quill about inquiries, applications, admits, deposits, enrollment, or revenueGenerate

Inquiry → applied → enrolled, by sourceDeposit rate by programCampus visit to applicationCounselor performance

What would you like to know?

Ask Quill any question about your inquiries, applications, admits, deposits, enrollment, or revenue. Every report is computed live from your CRM and SIS data.

How many deposits this week, against last week? How many first visits this week, against last week?

142 deposits, up 9%. Most of the rise came from referrals. 318 first visits, up 6%. Most of the rise came from referrals.

This week142 318

Last week130 300

4 secfrom question to answer, no analyst queue

The number it ownsAny report in under 10 seconds

3Co-innovation

Built with you, measured your way.

Our AI engineers work with your people to build AI around your rules, compliance and data, and agree up front what success looks like.

Co-build

We start where your journey loses the most people.

Prove

We try it on your live data against the goal we agreed.

Scale

What works rolls out to every team.

Outcome contract: Agreed · before purchase. Goal: First contact, day or night. Target: Under 60 seconds. Owner: Director of Admissions (Patient Access Lead for healthcare). Measured: On your live data, weekly. Illustrative example of a contract and its tracking.
LeadEdge AI Lab: Our AI engineers embed with your team. Your team (Admissions · IT · Compliance) and our AI engineers (Forward-deployed with you) work as one team: One team · your rules, your data. 01 Find the leak: Contacted → visited drops 36%. 02 Build it together: Agent built on your rules. 03 Test it live: Measured on your live data. Success agreed up front, before you buy.
Born in the Lab: Every standard agent started as a build with one customer. 01 Built with one customer: Your team + our AI engineers. 02 Tested live: Goal hit on live data. 03 Standard for every team: Ships to every customer. One customer’s build becomes a standard agent.
Agent Studio: Build agents yourself. Pick the trigger, set the rules, choose the action and switch it on. Same-day follow-up. 01 Trigger: Pick the event that starts it. New inquiry arrives. 02 Rules: Set the logic and the guardrails. Score above 80 · weekdays. 03 Action: Choose what it does in your CRM. Call within 5 minutes. 04 Deploy: Switch it on, supervise by exception. Alerts only on exceptions. Built by your team, no code.

The same journey, with LeadSquared AI

Same consumer. Three days, not three weeks.

The same ten moments. With an agent at every handoff, nobody waits for an answer and no leak stays open.

TodayTeam only

21 days9 leaks

With LeadSquared AIAgents + your team

3 days9 leaks plugged

The same ten moments, with LeadSquared AIAn agent on every leak

Book a demo

Show us your journey. We’ll show you where AI fits.

Thirty minutes, on a journey like yours.

Tell us where your journey leaks.
See the product that closes it.
Agree on what success looks like before you buy.

AI built for the way consumers buy. Which is never a straight line.

One consumer journey.

AI gets things done when it has context. Without it, it’s guessing.

Vertical depth

The whole journey

A partner that stays

Context is half the story. The other half is action.

One AI suite that sees and acts. Across the whole consumer journey.

AI does the legwork. Your team has the final say.

Know who to call first

Take the right next step

Turn every call into coaching

Skip the data entry

Ask a question, get the report

Agents that never clock out. Your team steps in where it matters.

Invorto

Flash

Sherlock

Nova

RevGuard

Hawke

Quill

Built with you, measured your way.

Co-build

Prove

Scale

Same consumer. Three days, not three weeks.

Show us your journey. We’ll show you where AI fits.

Products

Industries

Resources

Company

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