- Build time
- 4 to 7 days
- Visual motif
- Reasoning orbit
- Architecture basis
- SMS Reply Assistant Locked to Approved Templates uses a bounded agent handoff layer for AI Agents. An SMS agent that answers inbound texts using a library of pre-approved, compliance-safe message templates, filling in only the variable fields and... The architecture connects catalog the real recurring, twilio messaging service, gpt-5-class classifier, and agent handoff with an explicit control path.
SMS Reply Assistant Locked to Approved Templates
AI SMS
An SMS agent that answers inbound texts using a library of pre-approved, compliance-safe message templates, filling in only the variable fields and escalating anything off-script.
Build time 4 to 7 days
HMX Zone
ai agent case study
AI SMS
Verified HMX-owned case details.
outcomes
- Approved-only
- Replies stay on-brand and compliance-safe by construction
- Seconds to reply
- Common questions answered instantly, day or night
- STOP honored
- Opt-outs handled automatically at the carrier layer
- Human fallback
- Anything off-script lands in a staffed inbox
case architecture
SMS Reply Assistant Locked to Architecture
Catalog the real recurring
an intent classifier that
Twilio Messaging Service
GPT-5-class classifier
Human Escalation
Agent Handoff
- 01Catalog the real recurring
An SMS agent that answers inbound texts using a library of pre-approved, compliance-safe message templates, filling in only the variable fields and...
- 02an intent classifier that
Build an intent classifier that maps an inbound text to one template or to 'human needed'.
- 03Twilio Messaging Service
Twilio Messaging Service (A2P 10DLC) runs the bounded conversation step for SMS Reply Assistant Locked to while keeping tool use, transcripts, and escalation outcomes explicit.
- 04GPT-5-class classifier
Implement variable injection with strict validation so the agent can fill fields but never rewrite template body copy.
- 05Human Escalation
When automation confidence is low, route the record to a manual owner with the source, stage, and last action attached.
- 06Agent Handoff
Approved-only Replies stay on-brand and compliance-safe by construction; Seconds to reply Common questions answered instantly, day or night; STOP h...
problem and build
problem
The operating gap
Leads text in and expect a fast reply, but free-form AI texting risks off-brand wording, compliance problems, and missing opt-out language. Staff retype the same answers all day and still reply slowly outside hours.
build
What gets built
An agent classifies each inbound SMS into a known intent (hours, pricing range, booking, location, status) and responds with the matching approved template, injecting only safe variables like name or appointment time. Anything that does not map to a template, or that contains sensitive content, is held for a human. Every outbound message carries opt-out language, and STOP is honored automatically at the messaging-service layer.
build steps
- 01Catalog the real recurring questions and write approved templates with legal/brand sign-off, each tagged to an intent.
- 02Build an intent classifier that maps an inbound text to one template or to 'human needed'.
- 03Implement variable injection with strict validation so the agent can fill fields but never rewrite template body copy.
- 04Enforce STOP/HELP, quiet hours, and 10DLC registration at the Messaging Service level.
- 05Route unmatched or sensitive messages to a staff inbox with the suggested template as a draft.
- 06Log every send with the template ID used and add a weekly review of unmatched messages to grow the library.
architecture notes
Architecture layers
- Conversation layer: Catalog the real recurring questions and write approved templates with legal/brand sign-off, each tagged to an intent.
- Reasoning layer: Build an intent classifier that maps an inbound text to one template or to 'human needed'.
- Tools layer: Twilio Messaging Service (A2P 10DLC) runs the bounded conversation step for SMS Reply Assistant Locked to while keeping tool use, transcripts, and escalation outcomes explicit.
- Records layer: GPT-5-class classifier connects calls, messages, calendar work, or CRM writes while an agent classifies each inbound SMS into a known intent (hours, pricing range, booking, location, status) and responds with the matching approved...
- Escalation layer: Approved-only Replies stay on-brand and compliance-safe by construction; Seconds to reply Common questions answered instantly, day or night; STOP h...
Data flow
- Catalog the real recurring questions and write approved templates with legal/brand sign-off, each tagged to an intent.
- Build an intent classifier that maps an inbound text to one template or to 'human needed'.
- Implement variable injection with strict validation so the agent can fill fields but never rewrite template body copy.
- Enforce STOP/HELP, quiet hours, and 10DLC registration at the Messaging Service level.
- Route unmatched or sensitive messages to a staff inbox with the suggested template as a draft.
- Log every send with the template ID used and add a weekly review of unmatched messages to grow the library.
Controls and fallbacks
- Leads text in and expect a fast reply, but free-form AI texting risks off-brand wording, compliance problems, and missing opt-out language.
- An agent classifies each inbound SMS into a known intent (hours, pricing range, booking, location, status) and responds with the matching approved...
- When automation confidence is low, route the record to a manual owner with the source, stage, and last action attached.
Stack
- Twilio Messaging Service (A2P 10DLC)
- GPT-5-class classifier
- Approved template store (Twilio Content / DB)
- GoHighLevel
- Make or n8n router
- Opt-out + quiet-hours guardrails
research basis
back
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