Calls, business messaging and WhatsApp
tuntas.ai / ENTERPRISE AI CONSULTING & SOLUTIONS
AI SOLUTION TEAM READYTalk with an AI solution advisor↗tuntas.ai Enterprise AIBuilt for measurable results
10 enterprise scenarios · 6 shared AI capabilities · 4 deployment models
We design, build and deploy AI solutions for real enterprise work—not just roadmaps. Start with one high-value scenario, then scale across teams and functions.
Share one business priority. Our consultants will identify the first AI scenario worth implementing.tuntas.ai / AI CONSULTINGFrom one enterprise upgrade to transformation across the organization
FULL-SCENARIO AI SOLUTIONSDISCOVER · DESIGN · DELIVER
AI ACROSS THE ENTERPRISE
Ten enterprise scenariosbring AI into every moment of real work
From acquisition, service and management to production, healthcare, education and security, we begin with real workflows. Existing systems, AI capabilities and team collaboration are shaped into an operational loop that can launch and keep improving. Select a scenario to view its system prototype and delivery capabilities.
tuntas.ai · Marketing & sales growthEnterprise workspace connected
LEAD TO REVENUEAn intelligent loop from outreach to revenue and repeat businessHigh-intent leads enter a priority queue
Assign the right sales representative
No missed follow-up
Website, campaign and event leadsCalls, business messaging and WhatsAppCRM accounts and opportunitiesAI outreach and conversationAssign the right sales representativeIntent detection and lead scoringCreate follow-up tasksSales assistance and talk-track guidanceUpdate account and opportunity statusFaster responsesNo missed follow-upReviewable conversion journey
BUSINESS VALUEEvery lead has an intent score, an owner, a next action and a reviewable outcomeOpen today's priority opportunities
THE tuntas.ai AI CAPABILITY ARCHITECTURE
Shared AI capabilities, configured for your enterprise
Start with six reusable capabilities: conversation and voice, knowledge, documents, vision, decisions and AI assistance. Configure them around your data, systems, workflows, access rules and business goals. Choose SaaS, a dedicated environment, private deployment or a hybrid model.
TEN ENTERPRISE SCENARIOS
MarketingServiceManagementIndustryHealthcareRetail & hospitalityFinanceEducationAgricultureSecurity
Conversational & voice AI
Customer outreach · real-time guidance · multilingual service · conversation quality review
Enterprise knowledge
Knowledge base · permission-based answers · traceable sources
Document & content intelligence
Extract · classify · compare · draft · review
Vision & multimodal AI
Visual inspection · event detection · image and document understanding · evidence review
Prediction & decision intelligence
Demand forecasts · risk assessment · scheduling optimization · recommended next steps
AI assistants & automation
Task coordination · cross-team action · human confirmation · system updates
SHAREDShared AI capabilitiesA common set of models, knowledge, voice, vision and assistants that can support many scenariosCUSTOMIZEAI configured for your enterpriseChoose the capabilities that fit your data, systems, work processes, roles and business measuresDEPLOYMENTFlexible deployment and governanceUse SaaS, a dedicated enterprise environment, private deployment or a hybrid approachDELIVERYtuntas.ai consulting and implementationMove from clear upgrade priorities and a focused pilot to wider adoption and ongoing operations, while your enterprise stays in control
CLIENT FIELD NOTES
How AI enters real business
Four project records show where daily work was getting stuck. See how tuntas.ai introduced AI into each process. Learn what changed across customer service, retail, dealership growth and warehouse operations.
CMCHINA MOBILETELECOM RETAIL SERVICE
THE UPGRADED WORKFLOWArrival → AI identifies the need → approved guidance → staff confirmation → summary and task → accountable follow-up → result recorded
CLIENT PRACTICE · CHINA MOBILE CITY RETAIL CENTER
Service that continues beyond the counter: an intelligent upgrade for a China Mobile city retail center
PROJECT CONTEXT
The project covered reception, counter service and post-visit follow-up. Plan enquiries, device sales, complaints and business-customer needs often crossed several employees and existing systems.
BEFORE THE UPGRADE
Busy periods brought repeated plan and policy questions. Counter staff gave inconsistent answers on complex policies. Open requests often had no clear owner or due date after the customer left.
HOW THE SOLUTION WAS IMPLEMENTED
tuntas.ai connected approved service knowledge to an employee assistant. It identifies customer needs, retrieves the right policy and drafts a service summary. Staff confirm the summary. Open items then become tasks or tickets. Business-customer needs are assigned through CRM.
AI CAPABILITIES BUILT
Retail-service knowledge assistantConversation summaries and quality reviewAutomatic tasks for unfinished requestsBusiness-customer need identification and routing
IMPLEMENTATION OUTCOMES
A structured summary is ready as each enquiry endsService recordOpen items carry a named owner and due dateFollow-upRetail and follow-up teams work from the same customer recordCross-team work
HaierHAIERAPPLIANCE RETAIL & SERVICE
THE UPGRADED WORKFLOWMulti-channel enquiry → unified customer profile → home and budget needs → product-bundle draft → adviser approval → delivery and installation → after-sales record
CLIENT PRACTICE · HAIER REGIONAL RETAIL OPERATION
From customer needs to completed installation: connecting the full customer journey for a Haier regional retail operation
PROJECT CONTEXT
A Haier regional retail operation runs direct stores, dealer outlets and ecommerce service. It also handles live-stream and owned-channel leads. Before a sale, advisers confirm room, size, budget and product-bundle details. Inventory, delivery, installation and service follow.
BEFORE THE UPGRADE
The same customer appeared separately across channels. Advisers rebuilt product-bundle proposals by hand. Sales promises, delivery, installation and after-sales records remained disconnected.
HOW THE SOLUTION WAS IMPLEMENTED
tuntas.ai merged leads from every channel into one customer profile. It captured room, budget and category preferences. It then drafted product-bundle proposals from approved product information. After adviser approval, each plan continued into inventory, delivery, installation and after-sales service.
AI CAPABILITIES BUILT
Cross-channel customer profilesHome requirements and product-bundle proposalsAdviser follow-up and quotation assistanceDelivery, installation and after-sales coordination
IMPLEMENTATION OUTCOMES
Store and online enquiries merge into one customer profileCustomer leadsRoom requirements become an adviser-ready bundle planProposal preparationDelivery, installation and after-sales milestones return to the customer recordDelivery & after-sales
4SLOCAL AUTO DEALERSHIPAUTOMOTIVE DEALER OPERATIONS
THE UPGRADED WORKFLOWMulti-channel leads → match and remove duplicates → AI-assisted qualification → priority assignment → test-drive booking → purchase → service and next-purchase engagement
CLIENT PRACTICE · LOCAL AUTO DEALERSHIP
Bringing valuable leads forward: an AI-assisted sales upgrade for a local dealership
PROJECT CONTEXT
The dealership receives daily leads from automotive platforms, its website, short-form video, calls, visits and referrals. Each sale requires several follow-ups, a test drive and negotiation. The relationship then continues into service, insurance renewal and the customer's next vehicle purchase.
BEFORE THE UPGRADE
Duplicate and invalid leads were mixed with high-intent buyers. Response times varied by salesperson. Test drives, callbacks and customer preferences remained in private conversations instead of one shared record.
HOW THE SOLUTION WAS IMPLEMENTED
tuntas.ai matched duplicate leads across channels. AI-assisted outreach captured model, budget, timing and test-drive intent. High-intent buyers moved into a priority sales queue. Summaries, callback dates and appointments returned to CRM. The same record supports the relationship after purchase.
AI CAPABILITIES BUILT
AI-assisted outreach and intent captureLead matching and duplicate removalSales tasks and test-drive bookingService, insurance-renewal and next-purchase engagement
IMPLEMENTATION OUTCOMES
High-intent customers enter the sales queue firstLead priorityTest-drive promises and callback plans are recorded in CRMSales follow-upServicing, insurance renewal and the next purchase continue from the same customer recordPost-purchase journey
WHLOCAL LOGISTICS WAREHOUSELOGISTICS & FIELD OPERATIONS
THE UPGRADED WORKFLOWVideo and sensor alerts → event grouping → risk level → staff confirmation → assigned work order → resolution and review → evidence archived
CLIENT PRACTICE · LOCAL LOGISTICS WAREHOUSE
From seeing an exception to closing it: an AI operations upgrade for a local warehouse
PROJECT CONTEXT
The project covered a regional distribution warehouse from receiving and sorting to storage, loading and dispatch. Cameras, smoke detectors and equipment sensors were already in place. So were WMS records and manual inspections. These inputs did not yet feed one response process.
BEFORE THE UPGRADE
Control-room staff manually checked many camera feeds. Several alerts could describe the same event. Confirmed problems were assigned through group messages. Evidence, action and timing were not recorded together.
HOW THE SOLUTION WAS IMPLEMENTED
tuntas.ai grouped video events, sensor alerts and WMS records by time, location and task. It then assigned a consistent risk level. Staff confirm each event. The platform creates a work order for the right zone and shift. Photos, results and elapsed time are archived when work is complete.
AI CAPABILITIES BUILT
Aisle blockage and unsafe-work detectionSmoke, fire and equipment-event reviewWork-order assignment and overdue remindersAutomatic field-evidence records
IMPLEMENTATION OUTCOMES
One exception brings video, sensor and WMS evidence togetherException reviewConfirmed issues become tasks for the right zone and shiftAssigned work orderResolution photos, outcome and elapsed time are archived togetherField evidence
CORE TEAM
Business vision, industry experience and implementation expertise
A cross-disciplinary team with experience in enterprise strategy, international growth, foundation models and intelligent-product implementation.
Peter
Founder · AI strategyA Tsinghua University graduate and serial entrepreneur with experience in digital finance, digital marketing and enterprise growth. He connects opportunity assessment, pilot design and AI commercialization into a practical growth path.
Business strategy · Growth · New venture development
Sven
Global markets & growthBrings international-market experience from the Alibaba ecosystem, spanning regional strategy, channel partnerships, brand building and localized growth. He turns headquarters strategy into practical market-entry and customer-acquisition programs.
International expansion · Market entry · Localization
Nemo
Enterprise AI & foundation modelsFormer product director at China Mobile, responsible for foundation-model product planning, enterprise applications and large-scale implementation. His experience spans operator-grade knowledge assistants, intelligent customer service and workflow copilots, from architecture and data connection to rollout.
AI products · Platform architecture · Large-scale implementation
Leo
Intelligent products & implementationFormer intelligent-hardware lead at Dreame with end-to-end experience across product definition, supplier collaboration, hardware-software integration, validation and large-scale delivery.
Product strategy · Engineering collaboration · Operations
Ethan
Tencent AI technology leadAn AI technology leader at Tencent focused on foundation-model application architecture, agent engineering and enterprise AI platforms. His work spans knowledge assistants, intelligent service and operational analytics, including evaluation, data connection, access governance and production deployment.
Model engineering · Agent systems · Enterprise platformsCOMMON QUESTIONS
What enterprises ask before starting
Clear answers about scope, deployment and system integration.
01How does tuntas.ai start an enterprise AI project?+
We start with one business priority. We map the current workflow, data, systems and constraints. Together, we define the first measurable AI scenario and its implementation path.
02Which business areas can tuntas.ai support?+
We support ten scenarios: sales, service, management, manufacturing, healthcare, retail, finance, education, agriculture and security.
03Which deployment models are available?+
Choose SaaS, a dedicated environment, private deployment or a hybrid model. The choice depends on data sensitivity, network conditions and operating needs.
04Do enterprises need to replace their current systems?+
Usually not. tuntas.ai can connect existing business systems, files and accounts while keeping human approval and access controls in place.
Turn your next enterprise upgrade into an AI solution built for real work
Tell us which part of the business you want to improve. Share the systems your teams use and the result you need. The tuntas.ai solution team will identify the right starting point. We will map a practical path from one pilot to wider adoption.
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