AI customer service automation connected to your orders and CRM, with human hand-off
AI customer service automation is a support layer where AI chat answers routine questions and triages tickets using live order and CRM data, then hands anything sensitive or uncertain to a person with the full context. Netbase builds it as a growth capability, starting from its AI chatbot and WorkChat integrator module.
Review this solution for your workflow View relevant workReviewed by David (CEO) · Updated 17 Sep 2026
What the solution does, and where it stops
AI customer service automation is a support solution that helps customer service leads, e-commerce managers and operations teams answer more requests without making customers wait or repeat themselves. Customers ask in chat, email or a help form. The AI looks up their order, account or ticket history, answers what it can from approved content and live data, and sorts the rest into the right queue with a summary.
It stops where judgment is needed. Refunds, complaints, legal questions and anything the customer asks to escalate go to a person. The AI does not change orders or issue credits on its own; where an action is allowed, such as resending a tracking link, it runs through a defined tool with limits, and larger actions wait for staff approval.
This is a growth capability: the chat and integration modules exist in the Netbase library, but a customer-service AI case has not yet been published. The solution sits in the digital products family.
Where support teams lose time
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- Current state
- Agents answer "where is my order?" all day
- Target state
- Order status answered instantly from the order system
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- Current state
- Tickets land in one inbox and wait to be sorted
- Target state
- Each ticket classified, prioritized and routed on arrival
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- Current state
- Customers repeat their story after every transfer
- Target state
- Hand-off carries the conversation, order and summary
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- Current state
- Answers vary from agent to agent
- Target state
- Replies drafted from one approved knowledge base
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- Current state
- Nobody knows which questions could be automated
- Target state
- Reports show topics, resolution paths and hand-off reasons
How a support request is handled
The workflow, step by step:
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Greet and disclose
The chat tells the customer they are talking to an AI assistant and how to reach a person.
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Identify
The customer is matched to their account or order by login or a verified order reference.
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Understand
The AI classifies the request: order status, delivery, returns, product question, billing or complaint.
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Look up
It reads the order, shipping and CRM records it is allowed to see through read-only connectors.
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Answer or act
It answers from approved content and live data, or runs an allowed low-risk action such as resending a confirmation.
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Hand off
Sensitive, uncertain or escalated requests go to the right team with the transcript, customer record and a summary.
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Triage tickets
Email and form requests are tagged, prioritized and drafted as suggested replies for agents to approve.
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Learn
Agents rate AI answers and drafts; topics with poor results are fixed in content or rules and re-tested.
Capability modules
Customer messages on web or in-app → Converses and discloses AI use → Answers and hand-off requests
Login or order reference → Matches the customer securely → Verified session
Messages and tickets → Labels topic, urgency and sentiment → Routed requests
Verified customer → Reads order, shipping and account data → Live context for answers
Policies, FAQs, product content → Supplies approved answer sources → Consistent replies
Allowed requests → Runs limited, logged actions → Completed low-risk tasks
Escalations and drafts → Transfers with context; agents approve drafts → Faster human resolution
Transcripts and ratings → Scores answers, tracks topics and hand-offs → Improvement backlog
Traffic per channel → Applies quotas and budgets → Predictable running cost
The chat surface starts from the AI chatbot and WorkChat integrator, and the CRM and B2B sales engine and workflow automation toolkit supply customer records and routing where a client does not already have them. All three come from the Netbase productized module library.
AI in this solution
Where AI already runs in delivered work, and where it is offered as a growth capability.
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In delivered work
RAG knowledge assistant
Cited answers from company knowledge, the retrieval pattern a support assistant reuses; delivered for a client that is not named.
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In delivered commerce work
A recommendation engine
Suggests related products on 4over4's online printing store; not a support assistant.
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Available capability
NLP and generative AI for support conversations
Intent classification, grounded answers and reply drafting; not yet tied to a published customer-service case.
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Available capability
Approved support actions
Limited tools the assistant may run, with staff approval for anything larger; not yet tied to a published customer-service case.
Governance, integrations, data and deployment
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Human-in-the-loop points
Refunds, credits, complaints and legal topics always go to people. Agents approve AI-drafted email replies before they are sent until quality is proven on your data. Customers can ask for a person at any time.
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Transparency
The European Commission's summary of the EU AI Act says people using chatbots should be made aware they are talking to a machine, and states that the Act's transparency rules come into effect in August 2026. The assistant discloses itself in its first message.
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Evaluation
A test set of real past conversations is scored for correct answers, correct routing and correct hand-offs before launch and before each change, in line with the NIST AI Risk Management Framework.
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Access control and audit log
Connectors are read-only by default and scoped to the verified customer. Every answer, lookup, action and hand-off is logged. Following OWASP guidance on excessive agency, each tool has minimal permissions and any action that changes money or orders needs human approval.
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Data boundary
Customer and order data stay in your systems; the assistant reads them per request and does not copy them into model training. The model provider and retention settings are agreed in architecture; we work with models from OpenAI, Anthropic (Claude), Google (Gemini) and Meta (Llama), among other commercial and open-weight models.
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Cost limits
Rate limits per session and channel, caching of common answers and a budget alert guard against runaway use, a risk OWASP lists as unbounded consumption.
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Integrations
Netbase has delivered commerce on WooCommerce, Magento 2, Laravel and headless architectures, and works with Shopify, Salesforce and Odoo, the usual order and CRM sources. See the data and AI stack for tooling choices.
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Security
Netbase security practices apply from the design phase: secure code review, encryption in transit and at rest, role-based access with MFA and penetration testing, with NDAs and DPAs on request.
Implementation phases, roles and support
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Support audit
Analyse past tickets by topic, volume and resolution to find what can be automated safely.
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Design
Agree answer sources, allowed actions, hand-off rules, disclosure wording and metrics.
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Pilot
Launch on one channel and a few topics, with agents reviewing every AI answer.
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Expand
Add topics, channels and actions as test and live scores hold.
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Operate
Review ratings and hand-off reasons, and update content and rules.
A typical team combines a business analyst, a solution architect, AI and backend engineers, QA and a project manager; the feature engineering is our generative AI development service. The pilot stays lean, with a weekly review of real conversations alongside your support lead. The team works remote-first from Hanoi in English, overlapping Asia-Pacific days and European mornings (UTC+7), and connects helpdesk and order systems API-first. Human hand-off follows your own support hours. Where Netbase supports the solution after launch, support runs Monday to Saturday, with Sunday off. Most Netbase projects are delivered on fixed-price contracts, with scope and price agreed after the support audit.
Configuration, customization, IP and lock-in
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Configured
Topics, answer sources, hand-off rules, disclosure text, allowed actions, quotas and working hours.
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Customized
Connectors to your order, CRM and helpdesk systems, industry-specific flows and the agent desk.
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Ownership
You own the IP Netbase creates for your custom development; Netbase productized modules are licensed, not transferred. The model sits behind an interface and can be replaced.
Industry variants and use cases
Retail and e-commerce
Order status, returns, delivery and product questions; see retail and e-commerce.
Retail and e-commercePrint and custom products
Proof, artwork and production-status questions tied to each order.
B2B distribution
Account-specific pricing, stock and reorder questions for trade customers.
SaaS products
First-line product support with hand-off to technical staff.
Platform proof: Cloodo
Cloodo is one of the Netbase Business Divisions, alongside CMSmart, Printcart, Poslor and Storelly. It is an AI-powered digital workplace for company profiles, services, projects and team collaboration that connects internal staff and outsourced specialists in one hybrid workspace, with CRM, HRM, Cloud ERP and AI modules in one workspace. Netbase builds and runs it.
Cloodo is platform proof, not a customer-service case: it shows Netbase running an AI-enabled product where client communication, projects and CRM data share one workspace. No usage figures are published. Read the Cloodo Workspace record. For a client that is not named, Netbase also built a WhatsApp AI chatbot with CRM integration.
It puts company profiles, service listings, projects, tasks and team collaboration in one cloud workspace, beside CRM, HRM, Cloud ERP and AI modules, for internal staff and outside specialists alike.
Keep Reading
This anonymous portfolio record describes only the kind of AI system and what Netbase did; it publishes no client name, logo, location, dates, model choice, figures or results.
Keep Reading
OpenAI language models handle the conversation, an intent and flow layer keeps it on track, and leads, customer data and follow-up workflows stay in sync with the CRM.
Keep ReadingFrequently asked questions
Yes. The assistant says so in its first message and offers a person on request.
Not on its own. Money and order changes need staff approval.
We do not promise a figure. The pilot measures it on your own topics, and the scope grows from there.
Usually. The helpdesk and order systems are connected through their APIs, scoped in the design phase.
Services behind this solution
Generative AI development with evaluation and human review
Netbase builds generative AI features for product and operations teams: drafting, summarising, rewriting and content generation inside the software your people and customers already use. Every feature ships with an evaluation set, a human review step where output matters and limits on cost. Generative AI is a capability we are growing, and we label its maturity honestly.
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Related solutions and next step
Explore the other Netbase solutions or view relevant work. Send us a month of anonymized support topics and volumes, and we will review this solution for your workflow.
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