AI Concierge & Automation
An AI concierge that answers routine questions and hands complex enquiries to your team.
Who it helps
Hospitality, education, fitness and similar businesses with recurring questions on WhatsApp, Instagram or the website, a team that can approve the information the assistant uses, and the willingness to review what it says in the first weeks.
The problem it solves
An AI concierge that answers routine questions and hands complex enquiries to your team. For a villa, a school or a studio it means the routine questions that arrive every day, at every hour, are answered from your own approved information, and the ones that need judgment reach a person with the details already gathered.
The questions that arrive are mostly the same ones, and they arrive when your team is asleep or busy with a guest. An assistant that answers them from approved information, in the visitor's language where that is supported, and hands over the rest with the details already collected, leaves your team the conversations that need them.
It does not always know the answer, it does not complete every booking, it does not replace your staff, and it does not produce revenue by itself. It answers what it has been given, says when it cannot, and keeps a record of what people asked.
A guest of a fictional villa writes at 23:10 asking whether there is a baby cot. The assistant answers from the villa's approved facts, asks for the dates and the number of guests, and leaves the request with the manager for the morning. Fictional data.
A parent asks a fictional school about the enrolment age and next year's fees. The assistant gives the age range from the approved programme information, explains that fees are shared by the admissions team, and books a call-back with the details already noted. Fictional data.
A member of a fictional gym asks whether the Saturday class is full. If the class system is connected, the assistant answers from it; if it is not, it says so and passes the question to the front desk. Fictional data.
What you get
- The knowledge base
- Your business information collected, approved by you and kept current
- The conversation design
- Tone, scope, the questions it may answer, the moments it must hand over
- The connections
- The channels in scope, and the business systems that discovery confirms
- The handover rules
- Who receives what, with the details collected, and what the assistant says meanwhile
- The test round
- Your team asks the real questions before launch; what it fails on is fixed or excluded
- The reporting
- Enquiry themes and unresolved questions, in the agreed rhythm
How we approach it
What the assistant can take on depends on discovery and on what your systems actually support. The scopes we typically propose: answers grounded in approved business information; first qualification and routing of an enquiry; multilingual assistance where it is supported and tested; help with appointment or booking requests; connections to the business systems that matter; handover to a person when a question needs judgment or the information is not there; and reporting on the themes of enquiries and the questions that went unanswered.
Setting it up is a project with the business, not a switch. LARAS.tech builds the assistant from your approved knowledge, designs the conversations with Pakai Hati so they sound like your brand, connects the channels and systems that are in scope, tests the whole thing with your team before anyone outside sees it, and keeps improving it from what the reports show.
Channel availability, booking capabilities, access to pricing and the connections to your systems are specific to each implementation. A live deployment needs its own configured knowledge, its integrations, its operating rules and its privacy requirements, agreed before launch.
Who does what
- Pakai Hati
- Your contact for the whole project. Writes the conversations with LARAS.tech, so the assistant sounds like your brand.
- LARAS.tech
- Builds and operates the assistant from your approved information, connects the channels and systems in scope, tests it with your team before launch and improves it from the reports.
- You
What we need from you
- Your business information in writing, and one person who approves it and keeps it current
- Access to the channels in scope, set up as a business account, never a shared personal login
- A named person or team to receive handovers, with the hours they are available
- The privacy rules the assistant must follow, and the systems it may and may not read
How it works
Discovery
Which questions arrive, on which channels, who answers them today, and which systems hold the answers. What is in scope for a first version, and what is not.
Business knowledge
The information the assistant may use, written down and approved by you. Nothing it says comes from anywhere else.
Conversation design
How it greets, asks, answers and hands over, in your brand's tone and in the languages in scope. Pakai Hati writes with LARAS.tech.
Integrations
LARAS.tech connects the channels and the systems that discovery confirmed, each tested on its own.
Testing
Your team asks it the real questions, including the awkward ones. What it cannot answer is corrected or routed to a person.
Ongoing improvement
The reports show what people asked and where the assistant stopped; the knowledge and the rules are improved from them.
Not included
- An assistant that knows everything: it answers from approved information and says when it cannot
- Completing every booking or payment: that depends on the systems connected and the rules you set
- Replacing your staff: the assistant takes the routine and hands over the rest
- Revenue, conversion or satisfaction figures: reported where measurable, never promised
- Channels, languages and integrations that have not been tested for your deployment
Related projects
No project on this site uses an assistant yet; the examples above are fictional. LARAS.tech shows its own work on its own site.
Questions people ask
Which channels can it answer on?
That is decided in discovery, according to what each platform allows for your business and what you already use. Channel availability is specific to the implementation, not a given.
Can it answer in other languages?
Where a language is supported and has been tested with your content, yes. Each language in scope is tested before launch, not assumed.
What happens to our customers' data?
The privacy requirements are set before launch: what the assistant stores, for how long, who can read it and what it never asks. They are part of the operating rules, in writing.
Can we see an example of a conversation?
The examples on this page are written with fictional data to show the shape of a conversation. A real demonstration is set up on your own information during discovery.
The next step
It starts with a conversation about the business, the channels your enquiries come through and the questions you answer most. Next come a discovery session with LARAS.tech and a proposal that names the scope of the first version, the channels, the integrations and the operating rules.
AI Concierge & Automation is delivered in collaboration with LARAS.tech, an independent studio, which builds and operates the assistant.
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