Compa y Expa di g Existi g Fi tech Custome Ope atio s f om Huma -Assisted AI+BPO Towa d Auto omous AI Labo , with Pote tial fo Imp oved Ope ati g Efficie cy a d Ma gi s
Ta gets Deployme t of App oximately 300 AI Wo kfo ce U its fo a Si gle Existi g Custome by E d of Novembe 2026
SAN DIEGO a d SINGAPORE, Nov. 03, 2026 (GLOBE NEWSWIRE) — Helpo t AI Limited (NASDAQ: HPAI) (“Helpo t AI” o the “Compa y”), a global a tificial i tellige ce (“AI”) wo kfo ce i f ast uctu e compa y p ovidi g i tellige t commu icatio softwa e a d se vices to e te p ise clie ts, today a ou ced p og ess i t a sitio i g a established Southeast Asia fi tech custome f om AI-assisted busi ess p ocess outsou ci g (“AI+BPO”) ope atio s towa d auto omous AI Labo .
Buildi g o ea ly two yea s of collabo atio with the custome , Helpo t AI is expa di g the use of auto omous AI systems i debt-collectio ope atio s that have histo ically elied o a combi atio of AI tech ology a d huma age ts. The Compa y is ta geti g deployme t of app oximately 300 AI Wo kfo ce u its fo this si gle custome by the e d of Novembe 2026, as pa t of a b oade , o goi g t a sitio towa d auto omous AI Labo .
The i itiative ep ese ts a step i the Compa y’s st ategy to evolve f om p ovidi g AI-assisted se vices towa d delive i g AI wo kfo ce capacity capable of i depe de tly executi g busi ess wo kflows, with the pote tial to imp ove ope ati g efficie cy, educe elia ce o huma labo , a d suppo t highe -ma gi se vice delive y ove time.
Helpo t AI’s existi g elatio ship with the Southeast Asia fi tech custome cu e tly ge e ates app oximately $200,000 i mo thly eve ue, p ima ily th ough a AI+BPO ope ati g model that combi es AI-e abled tech ologies with huma age ts to suppo t debt-collectio activities. U de this model, huma age ts co ti ue to pe fo m ce tai custome i te actio s a d ope atio al fu ctio s, co t ibuti g to labo – elated se vice delive y costs.
The Compa y is p og essively t a sitio i g these ope atio s towa d auto omous AI Labo , i which AI systems pe fo m custome out each, commu icatio , egotiatio , follow-up, a d ope atio al eco dkeepi g, subject to app op iate complia ce ove sight a d exceptio -ha dli g p ocedu es. By educi g the eed fo di ect huma i volveme t i outi e ope atio al activities, Helpo t AI believes this t a sitio has the pote tial to imp ove se vice delive y efficie cy, educe labo – elated costs, a d suppo t highe g oss ma gi s ove time.
The t a sitio is expected to co ti ue beyo d Novembe 2026 as the Compa y expa ds AI Labo capabilities a d deployme t withi the existi g custome elatio ship a d pu sues simila oppo tu ities with additio al custome s.
Th ough o goi g live ope atio s a d multiple pe fo ma ce compa iso s, Helpo t AI’s AI Labo has demo st ated favo able esults elative to huma -ope ated teams i selected debt-collectio sce a ios. These esults eflect obse ved imp oveme ts i collectio efficie cy, custome e gageme t, a d ecove y pe fo ma ce as the Compa y’s AI models u de go fu the t ai i g a d optimizatio . Pe fo ma ce may va y depe di g o custome po tfolios, deli que cy stages, ope ati g co ditio s, a d othe facto s.
The Compa y believes these ope ati g esults suppo t the pote tial fo AI Labo to assume a g eate sha e of activities t aditio ally pe fo med by huma age ts, while mai tai i g app op iate complia ce ove sight a d huma i te ve tio whe e ecessa y. U like co ve tio al AI-assisted ope ati g models, i which AI p ima ily suppo ts huma employees, Helpo t AI’s auto omous AI Labo model is desig ed to execute defi ed busi ess wo kflows a d delive measu able ope atio al outcomes with educed depe de ce o di ect huma executio .
Based o ope ati g esults to date a d its established custome elatio ship, Helpo t AI is pu sui g pla s to expa d auto omous AI ope atio s ac oss ea ly-stage a d late-stage debt-collectio po tfolios, ta geti g deployme t of app oximately 300 AI Wo kfo ce u its fo this custome by the e d of Novembe 2026. This ta get applies exclusively to the Compa y’s ope atio s fo this si gle custome a d does ot i clude pote tial deployme ts with othe custome s.
The pla ed deployme t ep ese ts a expa sio of auto omous AI Labo capacity withi a existi g comme cial elatio ship athe tha the completio of the custome ’s t a sitio f om AI+BPO to AI Labo . The Compa y expects the t a sitio to co ti ue as additio al wo kflows a d ope ati g activities become suitable fo auto omous executio . The 300-u it deployme t ta get eflects the Compa y’s cu e t ope ati g pla s a d is ot a co t actual commitme t o gua a teed deployme t volume. Actual deployme t timi g a d scale will depe d o custome equi eme ts, ope atio al eadi ess, pe fo ma ce, a d othe facto s. Helpo t AI’s AI Labo busi ess utilizes a p edomi a tly pe fo ma ce-based settleme t model, li ki g eve ue to custome busi ess outcomes athe tha elyi g p ima ily o t aditio al seat-based p ici g.
The Compa y believes that expa di g auto omous AI Labo withi a established custome elatio ship may p ovide oppo tu ities to imp ove ope ati g leve age as AI systems assume a g eate p opo tio of activities p eviously pe fo med by huma age ts. The exte t a d timi g of a y esulti g ma gi imp oveme t will depe d o ope ati g costs, deployme t efficie cy, collectio pe fo ma ce, a d othe facto s.
Helpo t AI’s AI Labo capabilities a e suppo ted by a i teg ated p op ieta y tech ology a chitectu e desig ed to e able auto omous executio , wo kfo ce o chest atio , pe fo ma ce mo ito i g, a d co ti uous ope atio al imp oveme t. The Compa y’s co e tech ology e gi es, Hyp X a d Twi X, suppo t auto omous AI executio a d digital-wo ke capabilities, while K owFo ge, its i dust y k owledge a d expe t-expe ie ce t ai i g e gi e, is desig ed to t a sfo m the k owledge, decisio -maki g p ocesses, a d p actical expe ie ce of huma specialists i to capabilities that AI systems ca lea a d eplicate.
These tech ologies a e compleme ted by the Compa y’s AI Ope atio s Platfo m (AOP), which suppo ts wo kfo ce o chest atio , pe fo ma ce mo ito i g, a d ope atio al optimizatio , a d its U ified Commu icatio s Platfo m (UCP), which i teg ates voice calls, WhatsApp, Vibe , email, a d othe commu icatio cha els. Togethe , these platfo ms a e desig ed to e able AI Labo to execute custome e gageme t wo kflows, adapt i te actio s based o custome espo ses a d histo ical i fo matio , a d suppo t pe fo ma ce th ough o goi g ope atio al feedback.
The Compa y believes this i teg ated tech ology i f ast uctu e p ovides a fou datio fo expa di g auto omous AI Labo capabilities, sta da dizi g deployme t p ocesses, a d suppo ti g ope atio s ac oss multiple custome s a d ma kets.
Helpo t AI believes the t a sitio of a established, eve ue-ge e ati g custome f om AI+BPO towa d auto omous AI Labo p ovides a oppo tu ity to evaluate the ope atio al a d eco omic be efits of its evolvi g busi ess model i a eal-wo ld comme cial e vi o me t. Compa ed with t aditio al AI-assisted outsou ci g models that ely heavily o huma age ts, auto omous AI Labo may e able mo e efficie t deployme t, educed labo – elated delive y costs, a d g eate ope atio al scalability th ough ce t alized wo kfo ce ma ageme t a d sta da dized tech ology i f ast uctu e.
“Ou p og ess i Southeast Asia eflects a impo ta t step i the evolutio of ou busi ess f om AI-assisted ope atio s towa d auto omous AI Labo ,” said Gua ghai Li, Chief Executive Office of Helpo t AI. “By t a sitio i g a established custome elatio ship towa d a model i which AI systems i depe de tly pe fo m a g eate sha e of ope atio al activities, we see oppo tu ities to imp ove efficie cy a d educe elia ce o huma labo . Ou immediate focus is o expa di g deployme t a d st e gthe i g ope atio al pe fo ma ce, while co ti ui g to develop a scalable model that ca be exte ded to additio al custome s a d ma kets.”
The Compa y i te ds to co ti ue expa di g AI Labo deployme t withi its existi g fi tech custome elatio ship while pu sui g collabo atio oppo tu ities with additio al fi tech platfo ms i Southeast Asia a d othe i te atio al ma kets.
Helpo t AI expects to p ovide fu the updates, as app op iate, ega di g AI Wo kfo ce deployme t, ope atio al pe fo ma ce, a d comme cializatio p og ess as it co ti ues to develop AI Labo as a co e compo e t of its lo g-te m busi ess st ategy.
Helpo t AI (NASDAQ: HPAI) is a global AI wo kfo ce i f ast uctu e compa y p ovidi g i tellige t commu icatio softwa e a d se vices to e te p ise clie ts. Its co e asset is the AI Labo System, a i dust ial-scale platfo m desig ed to ma ufactu e, o chest ate, a d delive AI wo kfo ce capacity based o measu able busi ess outcomes.
Th ough its AI wo kfo ce, Helpo t AI helps clie ts d ive sales, imp ove e gageme t, a d educe costs. The Compa y’s missio is to t a sfo m huma expe tise i to scalable AI labo . Lea mo e at www.helpo t.ai.
Ce tai stateme ts i this a ou ceme t a e fo wa d-looki g stateme ts withi the mea i g of applicable secu ities laws. These i clude, but a e ot limited to, stateme ts ega di g Helpo t AI’s busi ess pla s, st ategies, objectives, a d expectatio s co ce i g the developme t, comme cializatio , adoptio , a d deployme t of AI Labo ; the t a sitio f om AI-assisted busi ess p ocess outsou ci g ope atio s towa d auto omous AI Labo ; a d the capabilities a d pote tial applicatio s of the Compa y’s tech ologies.
Fo wa d-looki g stateme ts also i clude the Compa y’s pla s to deploy app oximately 300 AI Wo kfo ce u its fo a existi g custome by the e d of Novembe 2026; expectatio s ega di g co ti ued deployme t a d ope atio al expa sio beyo d that date; a ticipated imp oveme ts i ope ati g efficie cy, labo – elated costs, g oss ma gi s, a d scalability; a d pote tial expa sio i to additio al custome s, i dust ies, a d geog aphic ma kets. The ta geted deployme t volume a d timi g eflect the Compa y’s cu e t ope ati g pla s a d expectatio s a d do ot ep ese t co t actual commitme ts o gua a teed outcomes. Actual deployme t levels, ope ati g pe fo ma ce, cost savi gs, a d fi a cial esults may diffe mate ially f om those a ticipated. Fo wa d-looki g stateme ts ca ge e ally be ide tified by wo ds o ph ases such as “believes,” “expects,” “a ticipates,” “estimates,” “p ojects,” “i te ds,” “pla s,” “ta gets,” “will,” “would,” “should,” “could,” “may,” o simila exp essio s. These stateme ts i volve k ow a d u k ow isks, u ce tai ties, a d assumptio s, i cludi g isks elati g to custome dema d, deployme t schedules, ope atio al pe fo ma ce, collectio outcomes, custome settleme t a a geme ts, egulato y equi eme ts, tech ological developme t, competitio , a d othe facto s that may affect the Compa y’s busi ess, fi a cial co ditio , a d esults of ope atio s. Actual esults may diffe mate ially f om those exp essed o implied by these fo wa d-looki g stateme ts. Histo ical pe fo ma ce esults f om specific custome deployme ts o ope ati g sce a ios should ot be co side ed i dicative of, o a gua a tee of, futu e pe fo ma ce o compa able esults i othe e vi o me ts.
The Compa y u de takes o obligatio to publicly update o evise a y fo wa d-looki g stateme ts to eflect subseque t eve ts o ci cumsta ces, except as equi ed by applicable law. I vesto s a e e cou aged to eview the Compa y’s fili gs with the U.S. Secu ities a d Excha ge Commissio fo additio al i fo matio ega di g isks a d u ce tai ties that may affect futu e esults.
I vesto Relatio sHelpo t AI LimitedEmail: i @helpo t.aiWebsite: i .helpo t.ai
