PutyourbusinessonAutopilotwithAIStaff
Stop stitching together n8n, Make, Vapi, and Retell. Your AI staff are voice and text agents you draw on one canvas — with the phone network built in, 3,200+ apps a click away, and flows that double back and fix themselves instead of going quiet.
- Latency
- SUB-1.2S
- Rate
- $0.08 AUD/MIN
- Integrations
- 3,200+
- Channels
- VOICE + TEXT
Talk to Loxley
Press to open a live line
- Transport
- WEBRTC
- Model
- REALTIME
- Region
- AU-SE
- Graph
- VOICE + TEXT
What makes it different.
Talk or type, one canvas
The same flow answers the phone and replies to a text. Telephony is native — direct SIP trunking through Twilio and Telnyx, not a reseller hop bolted on afterwards.
Recovers instead of failing
Flows can loop. When a plan falls through mid-conversation, the agent doubles back and tries the next one rather than apologising and hanging up.
Tested before it answers
Langoedge reads your agent's instructions and writes the test cases itself, then runs them as simulated callers — so you find the gaps before a customer does.
Your agent doesn't give up when plan A fails.
Most voice platforms run a straight line. The moment reality doesn't match the script, the caller gets an apology and a dial tone. Langoedge compiles your canvas into a real state machine, so an agent can double back, try again, and finish the job.
Loops instead of dead ends
Slot taken? The agent routes back and tries the next one. Graphs are optionally cyclic, so recovery is part of the flow rather than an exception you have to code around.
A second model on the gate
Branch conditions can be gated by a supervisor model that checks the agent's reasoning before the flow moves on, with optional human approval before anything is committed.
Picks up where it left off
State is written at every step and never overwritten, so an interrupted run resumes from the last good point instead of starting the conversation over.
Linear script
The usual outcome
- Caller asks for 3:00pm
- Slot is already booked
- “Sorry, I can't help.”
Call lost
Langoedge graph
Same problem, handled
- Caller asks for 3:00pm
- Slot is already booked
- Check next opening — 3:30pmLoops back
- Booked, confirmation sent
Appointment booked
The work happens while the agent keeps talking.
A voice agent that stops to think sounds broken. Langoedge keeps the conversation loop light and pushes the heavy lifting into background flows, so your caller hears a person doing their job rather than a machine buffering.
Background sub-flows
CRM writes, database lookups, and slow API calls run as a separate flow mounted inside the live call, so the conversation never waits on them.
No dead air
While a tool runs, the agent covers the gap with natural conversational filler and ambient sound instead of an unnerving silence.
Work continues after hang-up
The moment a call ends, the transcript can trigger a follow-up flow: notes written back, a recap texted, the next task created.
Remembers across conversations
Switch on long-term memory and the agent keeps preferences and context between conversations instead of starting cold every time.
Integrations
Connect the tools you already run. Write no glue code.
Adding a new tool to an agent should be a setup step, not an engineering project. On Langoedge it is.
3,200+
apps, wired in from configuration alone
Langoedge reaches your stack through Pipedream Connect, so the catalogue is discovered live rather than hard-coded into a shortlist someone has to maintain. Gmail, Slack, HubSpot, Airtable, Google Sheets, your CRM — a tool your agent can call is a few clicks, not a sprint.
Tool catalogues are cached on our side, so your agents keep working through an upstream hiccup.
Native integrations
Deep, hand-built support for the systems our verticals live in.
- Cliniko
- ServiceM8
- Twilio
- Telnyx
- Pinecone
- Qdrant
Purpose-built where it counts
The systems a vertical actually runs on get hand-written integrations rather than a generic wrapper — Cliniko for practices, ServiceM8 for trades, Twilio and Telnyx for the phone network itself.
Your own data, your own keys
Point agents at your SQL databases or run retrieval over your own documents with Pinecone or Qdrant. Bring your own model and vector keys so sensitive data stays on infrastructure you control.
An escape hatch for developers
Custom Python nodes, direct SQL, and raw HTTP calls sit on the same canvas as everything else. No-code is the default, not the ceiling.
Built for
A general platform, with specialist depth.
Langoedge builds any agent you can draw. In these four sectors we went further and built the integrations by hand, so the agent speaks your systems on day one.
Healthcare
Patient intake that never rings out
Answer every call to the practice, find the patient, book or move the appointment, and write the summary back once the caller hangs up.
- Book, move, and cancel appointments
- Look up existing patients on the call
- Post-call notes written back automatically
Native Cliniko integration
Trades & field service
After-hours calls become jobs
Capture the job details, triage the urgency, and get the booking on the board instead of losing it to voicemail.
- Qualify and log the job
- Text back every missed call
Native ServiceM8 integration
Recruitment
First-round screening at volume
Screen inbound candidates on the phone, capture structured answers, and push the shortlist into your ATS.
- Structured phone screens
- Availability and rate capture
Property
Every enquiry answered
Handle listing enquiries, qualify tenants against your criteria, and book inspections without an agent on the phone.
- Tenant qualification
- Inspection booking
Stop listening to call recordings.
Quality assurance on voice agents usually means somebody spending their afternoon with a headset on. Langoedge tests the agent for you — before launch and on every call after it.
Simulated callers
Give an AI caller a persona and a scenario and let it work your agent end to end — before you point a real phone number at it.
Scored automatically
Define the metric, the threshold, and the prompt. Every real call gets judged against your criteria and rolled into a pass rate and a quality score.
Test cases you didn't have to write
Langoedge reads your agent's instructions and drafts the personas and scenarios itself — happy paths, edge cases, and the ways it could fail. They stick around as you edit, so you can re-run them after every change.
Example evaluator
Patient intake — last 250 calls
94/100
Quality score
- Captured date of birth96%
- Confirmed appointment time92%
- Followed consent script100%
- Escalated when uncertain88%
Illustrative report. You define the metrics and the thresholds.
Jobs your AI staff can start on Monday.
Hiring for phone coverage means job ads, training, and a rota that still leaves evenings and weekends uncovered. An agent takes the first pass at all of it from the day you switch it on — and hands you the calls that genuinely need a human.
Answer the phone
Every call picked up, including the 7pm one.
Follow up by text
Reminders, recaps, and a reply to every missed call.
Work the systems
Look records up mid-call and write them back after.
Qualify and route
Screen the caller, escalate the ones that need a person.
Serious controls, without the rollout.
Handing business decisions to software means being able to prove what it did. Langoedge is built so the answer to “what happened on that call?” is a link, not an investigation.
An audit trail you can actually read
Because every run is checkpointed, each decision leaves a record: what the agent knew at that moment, which branch it took, and which tool it called. When someone asks why an agent did something, you can answer with evidence instead of a shrug.
Your data stays yours
Bring your own model and vector database keys. Resources are isolated per user, and deletes are soft, so nothing disappears irrecoverably.
Locked down by default
Authenticated access, cryptographically signed service-to-service calls, tiered rate limiting, and outbound request filtering so an agent can't be talked into reaching your internal network.
Deploy where your people already are
A phone number, an SMS thread, a branded portal, a chat widget, or an in-app copilot on web, mobile, or desktop — the same agent, wherever the conversation starts.
Early results.
From the first teams putting Langoedge agents to work.
“Our Langoedge AI agent for creating vendor reports has completely transformed our workflow. We were able to save over 15 hours per report, allowing our sales team to focus entirely on closing properties.”
“Integrating Langoedge's Voice AI into our research projects has been incredibly rewarding. The natural voice interactions provided realistic simulation environments that were highly beneficial for training our trainees.”
Head to head
The same job, four ways.
Every option below can answer a phone. The differences show up on the calls that don't go to plan.
| Category | Off-the-shelf AI tool | n8n + Vapi stack | Custom build | Langoedge |
|---|---|---|---|---|
| When the plan fails | Apologises and ends the call. You find out from the voicemail. | The webhook errors and the caller hears silence. | Whatever recovery logic someone remembered to write. | Loops back, tries the next option, and escalates to a human only when it is genuinely stuck. |
| Response speed | A fixed pipeline you have no way to tune. | Every tool call is a webhook round trip the caller waits through. | Fast if you build it right — and months before you find out. | Direct SIP trunking plus background sub-flows, built to a sub-1.2 second target. |
| Getting it built | Locked to fixed features. Hard to shape around how you work. | Webhooks, API keys, and JSON parsing wired between three systems. | Specialist engineers and a roadmap measured in quarters. | Draw the flow, test it, point a number at it. Most agents go live in a single session. |
| Seeing what it did | A recording and a hunch. | Three dashboards to correlate before you find the failure. | You build the observability layer too. | One timeline per run: the transcript, the branch it took, and every tool it called. |
| Testing it | Ring it yourself and hope. | Manual test calls, no scoring, no regression safety net. | Build a test harness before you can trust a single change. | Simulated callers before launch, automatic scoring against your own criteria after it. |
| What it costs | Per-seat pricing that climbs every time the team grows. | Three subscriptions: workflow tool, voice platform, model provider. | Salaries and maintenance that never stop. | $0.08 AUD a voice minute and $0.002 a tool call. No base fee, no seats, no contract. |
Transparent, usage-based pricing.
Only pay for what you actually use. No hidden fees or lock-in contracts.
Free Tier (Start Building)
Everyone getting started with Langoedge.
What's Included:
- Text Agents: Unlimited text messages (BYOK required for LLM/Pinecone).
- Tool Calls: 100 free tool calls / month (e.g. database lookups, webhooks, scraping, custom code executions).
- Vector Storage (RAG): Unlimited storage/queries (BYOK required).
- Voice Agents: 5 minutes of free web-voice testing.
- Support: Community Reddit/Forum.
Pay-As-You-Go (Scale Infinitely)
Businesses and developers deploying active agents to production.
How it Works: Simply add a credit card to unlock unlimited scaling, production voice features, and tools.
In plain terms: you're billed only for the voice minutes and tool calls your agent actually uses. Nothing is metered until you go past the free monthly quota.
- Text Agent Tool Calls: $0.002 AUD per tool call (billed after exceeding the 100 free monthly quota). Includes web scraping, custom Python code execution, CRM syncing, database operations, or external webhook calls.
- Voice Minutes: $0.08 AUD per minute.
- Basic Text Messages (No tools): Still Unlimited (BYOK).
Build your first agent
this afternoon.
The free tier needs no card. Draw the flow, ring it yourself, and see whether it holds up — before you decide anything.
- No credit card
- No per-seat pricing
- Bring your own keys
Frequently asked questions
The things people ask before they build their first agent.
Langoedge is one visual canvas for building AI staff that talk on the phone, answer texts, and do real work in your business systems. You draw the flow; Langoedge compiles it into a real state machine and runs it on native telephony. There is no separate workflow tool, voice platform, and glue layer to keep in sync.
In a stitched-together stack, your voice platform has to call out to your workflow tool over a webhook and wait for the answer, which is where dead air and dropped context come from. In Langoedge, conversation state, database access, and telephony live on the same canvas, so there is no round trip. You also get one set of logs instead of three separate dashboards to correlate when a call goes wrong.
This is the core of how Langoedge is built. Most voice platforms run a linear script: if the booking slot the caller wanted is already taken, the agent apologises and the call dies. Langoedge graphs can be cyclic, so the agent loops back, tries the next available slot, and only escalates to a human when it genuinely cannot resolve the request. Conditional branches can also be gated by a second supervisor model, with optional human approval before an action is committed.
Over 3,200 apps through Pipedream Connect, wired in from configuration rather than custom code, so adding a new tool is a setup step rather than an engineering project. On top of that, systems where a generic wrapper is not good enough get purpose-built integrations, including Cliniko for healthcare practices and ServiceM8 for trades and field service. Agents can also query your SQL databases, run retrieval over your own documents, call any HTTP API, and execute sandboxed Python.
Langoedge connects to the phone network through direct SIP trunking with Twilio and Telnyx rather than hopping through a reseller, and the voice loop is kept deliberately light by pushing heavy work to background sub-graphs. The platform is built to a sub-1.2 second response target. During longer tool calls, the agent uses natural conversational filler and ambient sound rather than going silent.
Two ways, and neither involves listening to recordings all afternoon. You can spin up a simulated caller with a persona and a scenario and let it exercise your agent end to end. And you can define your own evaluation criteria, metric, threshold, and prompt, and have every real call scored automatically against them, rolled up into a pass rate and a quality score.
A voice agent can automatically fire a text graph the moment the caller hangs up, using the transcript as its input. That is how post-call work gets done without keeping the caller on the line: writing a visit summary back into your practice management system, sending a recap text, creating the follow-up task, or updating the CRM record.
Yes. Long-term memory is a per-agent setting: turn it on and the agent stores what matters — preferences, context, the details you tell it to keep — and recalls them in later conversations rather than starting cold every time. Memories are namespaced to your account and persisted in the database, separately from the short-lived state of any single run, and the agent can add to them or clear them as part of your flow.
No. Building, testing, and launching an agent is a visual, drag-and-drop process, and most agents go live in a single session. There is an escape hatch when you want it, though: custom Python nodes, direct SQL, and raw API calls sit on the same canvas, so a developer on your team is never boxed in.
Yes. Phone numbers can be bound directly to a text agent for inbound SMS, and the same graph logic runs whether the conversation arrives by voice or by message. Missed calls are de-duplicated and can trigger an automatic text follow-up, so an unanswered call still becomes a conversation instead of a lost lead.
There is a free tier with unlimited text messages, unlimited vector storage on your own keys, 100 tool calls a month, and 5 minutes of web voice testing. Beyond that it is usage-based: $0.08 AUD per voice minute and $0.002 AUD per tool call, with no base fee, no per-seat pricing, and no lock-in contract.
Langoedge is built with enterprise controls in mind: authenticated access with per-user resource isolation, signed service-to-service calls, rate limiting, soft deletes, and a checkpointed execution history that gives you an audit-ready record of every decision an agent made and why. You can also bring your own model and vector database keys so sensitive data stays on infrastructure you control. If you have specific compliance requirements, talk to us about your environment before you deploy.