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Lavenity
Summary
Most service businesses run their front office across a notebook, a CRM that nobody updates, and whoever picks up the phone first — and every new enquiry risks becoming a duplicate job, a missed detail, or a booking that lands on a technician who doesn't cover that zone.
Lavenity puts an AI agent called Ven in front of every inbound message — across website chat, email, WhatsApp, Telegram, and Instagram — and runs the same qualification loop your team already does: address, equipment, fault, access, policy check, then a proposed slot from real availability. Ven proposes; your operator accepts or rejects before anything is sent or booked. Confirmed visits become work orders with full context attached. The audit log records whether Ven or a person made each move, and whether policy blocked a booking before it reached the customer. The reporting answers the question owners actually care about: did conversations turn into work orders.
Bottom line: Pick Lavenity if you're running field service visits and losing jobs to slow qualification or double-handling enquiries across channels — but if you need API access to push work orders into an existing FSM platform, the integration story isn't there yet.
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Pros
Sign in to edit- All inbound channels — website chat, email, WhatsApp, Telegram, Instagram — land in a single queue, so a customer who messages on one channel and sends a photo on another doesn't split into two jobs that get handled separately.
- Returning customer records include property address, installed equipment, serial number, and the log of previous visits, which means the technician leaves the yard already knowing what was found last time — eliminating the pre-visit phone call.
- Availability shown to customers is drawn from actual working hours, technician skills, service zones, and travel buffers, so you are never booking a slot that doesn't exist or a technician who doesn't cover that area.
- Every action is logged — what ran, whether Ven or a person did it, and whether policy blocked the request — so when a customer asks why they were turned down, the record is already there.
- Operator approval is required before any proposal reaches the customer, which means Ven cannot promise a slot, confirm a visit, or send a quote without a person signing off first.
Cons
Sign in to edit- No API is available, so confirmed work orders cannot be pushed automatically into an external scheduling, billing, or FSM platform. Teams that need that handoff between systems are left copying data manually — and once the volume of jobs makes that untenable, they move to a platform with native integrations.
- No self-hosted option exists. For operators under data residency requirements or handling customer records that cannot leave a specific jurisdiction, Lavenity is off the table before the trial ends.
- The qualification and scheduling loop is built around the service templates you configure — if your service catalogue is large, highly variable, or changes frequently, maintaining those templates becomes an ongoing operational task that sits outside the tool's automation.
About
- API Available
- No
- Self-Hosted
- No
- Last Updated
- 2026-09-09T07:02:49.612Z
Best For
Who it's for
- Service businesses handling field visits
- Teams managing recurring maintenance or repair jobs
- Operators who want AI assistance with approval gates
What it does well
- Qualifying service enquiries from multiple messaging channels
- Scheduling technician visits based on real availability and skills
- Generating work orders with full context at confirmation
- Enforcing policy rules on service eligibility and access
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Sign Up to ContributeFrequently Asked Questions
- Is Lavenity free?
- Lavenity has a permanent free tier alongside paid upgrades. You can keep using a baseline version indefinitely without paying.
- Is Lavenity open source?
- No — Lavenity is a closed-source tool. Source code is not publicly available.
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Lavenity is a front-office layer for service businesses that handles the gap between an inbound message and a technician on the calendar. The AI agent Ven qualifies every enquiry by extracting address, equipment details, fault description, and access instructions — flagging which answers the customer provided and which were inferred. Once qualification is complete and policy rules pass, Ven proposes a slot drawn from actual working hours, technician skills, service zones, and travel buffers. Your operator reviews the proposal field by field and approves or rejects before anything reaches the customer. On confirmation, a work order is generated with the full context attached.
The differentiating feature is the operator approval gate built into every proposal. Nothing is promised, sent, or booked on Ven’s initiative alone. This is not a concession — it is the architecture. The docs describe each service template as defining what ‘ready to book’ means: required questions, default duration, eligible zones, required skills. Policy enforcement is logged per request, including the cases where a booking was blocked, so you have a record if a customer disputes the outcome.
Lavenity fits teams where the front-office bottleneck is the qualification and scheduling loop — recurring maintenance, repair visits, any service where the same four or five questions determine whether a job can be booked. It fits less well when your operation requires pushing confirmed work orders into an existing field service management platform via API, or when you need to self-host for data residency reasons. No API and no self-hosted option are listed anywhere in the vendor’s documentation. Teams that need confirmed jobs to flow automatically into a separate scheduling or billing system will find themselves copying data manually or hitting a hard wall.