KivvaTech

How Acquire.io Scaled to Fortune 500 Clients with Rebuilt Cobrowse and AI Chat

Rebuilt the core cobrowse engine, AI chatbot, and video infrastructure for a unified customer engagement platform serving 25+ languages across global enterprise accounts.

Acquire.io is a unified customer engagement platform combining live chat, cobrowse, video chat, AI chatbot, and SMS into a single agent workspace. Used by Fortune 500 companies including leading US financial institutions, Acquire.io needed to scale its core technical infrastructure to meet enterprise SLAs, expand AI chat capabilities, and deliver consistent video quality across varying network conditions worldwide.

60%

reduction in first-response time

40%

support queries resolved by AI

25+

languages with full platform support

3

Fortune 500 top-10 US banks as clients

The challenge

Acquire.io had strong product-market fit and notable enterprise clients, but three core technical areas were creating friction at scale: the cobrowse engine used significant CPU on agent machines, degrading chat responsiveness; the chatbot could not handle multi-turn conversations or route to human agents with context intact; and video chat quality was inconsistent for international users on variable connections. Enterprise clients were requesting 25-language support that went far beyond what was operationally feasible with their existing i18n approach.

Cobrowse engine creating CPU spikes on agent machines

Screen synchronisation was rebuilding the full DOM on every update. During active cobrowse sessions, agent machines saw CPU usage spike to 80%+, causing the chat interface to stutter and degrading the experience for both agent and customer.

Chatbot failing on multi-turn conversations

The existing rule-based chatbot could handle simple FAQ queries but failed on anything requiring context from earlier in the conversation. Handoff to human agents lost all conversation context, forcing customers to repeat themselves.

Video quality degrading on international connections

WebRTC sessions between enterprise clients in Southeast Asia and North America were experiencing high packet loss, frozen frames, and dropped calls. No adaptive bitrate or regional TURN infrastructure was in place.

i18n coverage too shallow for enterprise requirements

Platform UI existed in 8 languages. Enterprise clients were requiring full coverage across 25 languages including Arabic (RTL), Japanese, Korean, and 6 European languages for global support operations.

What we built

We rebuilt four core systems in parallel: a CRDT-based cobrowse engine that transmits DOM deltas rather than full snapshots, an AI chatbot with intent recognition and CRM-integrated agent handoff, a WebRTC stack with adaptive bitrate and regional TURN infrastructure, and a scalable i18n pipeline covering 25 languages with RTL support. All four shipped within a 5-month engagement.

01

CRDT-based cobrowse engine

Replaced the full-DOM-sync approach with a Conflict-free Replicated Data Type (CRDT) model that transmits only DOM mutations over a WebRTC data channel. CPU usage during active cobrowse sessions fell by 75% on agent machines. Latency dropped from 400ms to under 60ms.

02

AI-powered chatbot engine

Context-aware intent recognition with slot filling across conversation turns, trained on Acquire.io's client conversation history. Seamless CRM-integrated handoff to human agents that passes the full conversation transcript, intent summary, and customer record. Handles tier-1 queries autonomously with escalation paths for complex cases.

03

Adaptive WebRTC video infrastructure

Dynamic bitrate adaptation based on measured packet loss and bandwidth, dropping gracefully from HD to SD to audio-only rather than dropping the call. Regional TURN relay servers deployed in Singapore, Frankfurt, and Ohio to serve global enterprise clients within acceptable RTT budgets.

04

25-language i18n platform

Automated translation pipeline with professional review workflow, RTL layout support for Arabic and Hebrew, locale-aware date, number, and currency formatting, and a QA testing suite that runs the full UI in each locale before release. Chatbot content translated and intent-matched per language.

05

Enterprise analytics and compliance dashboard

Agent performance metrics, CSAT scoring, session replay with PII masking, conversation-level analytics, and configurable routing rules. Compliance controls for SOC 2 and GDPR including data residency selection and automated retention policy enforcement.

Results

Measurable outcomes delivered, not projected.

60%

first-response time reduction

The AI chatbot handles tier-1 queries instantly, reducing average first-response time across all channels by 60%. Enterprise clients reported measurable improvement in CSAT scores within 30 days of deployment.

40%

AI resolution rate

40% of all inbound support queries are now fully resolved by the AI chatbot without agent involvement. Agent capacity freed by automation has been redirected to higher-value complex queries.

75%

CPU reduction in cobrowse

CRDT-based cobrowse engine reduced agent machine CPU during active sessions from 80%+ to under 20%, eliminating the performance degradation that was impacting chat quality during simultaneous sessions.

25+

languages fully supported

Full platform coverage across 25 languages opened enterprise contracts in markets where Acquire.io previously could not bid. Three top-10 US banks now use the platform for their global support operations.

Technologies used

Real-time

WebRTCCRDT syncTURN infrastructureWebSocket

AI / NLP

PythonIntent recognitionSlot fillingCRM integration

Frontend

ReactTypeScripti18n / RTLTailwind CSS

Infrastructure

AWSMulti-regionKubernetesRedis
KivvaTech took on some of the hardest engineering problems in our platform and delivered cleanly. The cobrowse rebuild alone changed the conversation we were having with enterprise procurement teams.
V

VP of Engineering

Acquire.io

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