We build the AI employees that do your most expensive repetitive work — and we run them for you.
Front desk and back office. They answer leads in seconds, pick up the phone after hours, triage your inbox, and keep your CRM clean — managed on our infrastructure, monitored, and tuned every month. And they learn from every correction your team makes.
Replying to every inbound lead in under a minute, answering the phone at 9pm, keying invoices, deduping the CRM — it is exactly the repetitive work that burns out staff and leaks revenue. An agent that never sleeps does it; your team does the work that needs a human.
Most AI projects fail in production because they are sold as set-and-forget and quietly break. We don't hand you a bot. We run real agents on infrastructure we already operate, with a human review queue and a monthly tuning loop — the part the cheap bots structurally can't do.
Every correction your team makes becomes a reusable example. A scheduled evaluator proposes playbook improvements you approve. Errors tighten the guardrails and escalate to a human. The agent's accuracy climbs and your review time shrinks — measurably, in the dashboard.
Ten AI employees, two teams.
Each agent owns one job, knows exactly which tools it may use, escalates what it shouldn't handle, and is judged on a single outcome metric. Start with one. Add the rest as they earn it.
🛎️ Front desk customer-facing
The revenue-recovery wedge — these capture and convert the leads and calls you're losing today. They sell fastest because the result shows up in week one.
Replies to every inbound web form and SMS lead in under 60 seconds — qualifies, answers the first questions, and books the appointment before a competitor can.
The instant a call goes unanswered, it texts the caller back, offers to help or book, and routes anything complex to a human — so a missed call stops meaning a lost patient.
Answers your phone in a natural voice, handles common questions, books straight into your calendar, and escalates anything it shouldn't take — day, night, and overflow.
Runs structured intake for new patients, clients, or leads — collects the right fields, checks criteria or insurance basics, and hands a clean, qualified record to your team.
Asks happy customers for a review at the right moment after a visit, routes feedback to the right place, and steers unhappy notes to a human before they go public.
🗂️ Back office internal ops
The stickiness layer — these reclaim the hours your team loses to admin. They expand the engagement once a front-desk agent has proven the model.
Sorts inbound email, drafts replies in your voice into a review queue, and trashes obvious junk — so the inbox is handled before you open it.
Dedupes contacts, fills missing fields, tags records, and logs every interaction — keeping the database you make decisions from actually trustworthy.
Reads invoices and receipts, turns them into structured entries, and drops them in a review queue for sign-off — replacing the repetitive bookkeeping keying.
Compiles your pipeline, inbox, bookings, and key numbers into a single morning brief — so you start the day knowing exactly what needs you.
Optimizes bookings, fills cancellation gaps from the waitlist, and chases no-shows back onto the calendar — recovering slots that would otherwise vanish.
The performance figures above are directional industry benchmarks for the category, not guarantees for your specific business. Your engagement is tied to a measured outcome we agree on up front — see the guarantee in pricing.
How they learn from feedback and errors — honestly.
This is the question that separates a real service from a course-seller's bot, so here is the plain truth: this is not model fine-tuning, and we will never claim it is. "Learning" here is three concrete, buildable mechanisms working together.
Every agent proposes its work — a drafted reply, a proposed booking — into a review queue. When your operator edits or approves it, that exact correction is saved as a labeled example in the agent's memory. The best examples are fed back into the agent's context, so the same mistake doesn't happen twice. Accuracy climbs week over week; your review time shrinks.
Every action logs an outcome — booked, converted, satisfied, errored. A scheduled evaluator agent reviews those outcomes against the benchmark for that agent, finds the patterns behind what's working and what isn't, and writes a proposed playbook revision. It is versioned, and a human approves it before it ever goes live — with one-click revert.
When a tool fails, confidence is low, or an output is flagged, it's captured as an error record — and the agent escalates to a human with full context instead of failing silently. Recurring errors automatically propose a tighter guardrail we review. Add per-contact and per-client memory, and the agent genuinely remembers your business and your customers.
In one sentence: learning = memory + few-shot examples from your corrections + an evaluator that proposes human-approved playbook revisions + guardrails that tighten as errors appear. No self-training overclaim, no black box — and it's exactly what makes an agent get better the longer it works for you.
What does one agent pay back?
Estimate the cost of the repetitive task you'd hand to a single Starter agent — then see the monthly saving and the payback against the $500/mo plan. No email required; the numbers update as you type.
- ▸ Count the tasks one agent would take off your team each week.
- ▸ Estimate the minutes each one really costs, end to end.
- ▸ Use the loaded hourly cost of whoever does it today.
At these inputs, one agent more than covers its $500/mo and recovers the $1,000 setup. And this counts only reclaimed labor — not the leads recovered or appointments saved, which is usually the larger number.
Request a pilot for this →Three tiers. Land small, expand later.
All prices in USD, confirmed before any work starts. A low floor and a fast yes — start with one outcome-guaranteed agent and add the rest once it has earned the trust. No long-term contracts; cancel the monthly anytime.
- ▸ One managed agent, run for you
- ▸ A measured target — hours saved or leads recovered — in 30 days, or your setup fee back
- ▸ Human-in-the-loop review + the learning loop
- ▸ Monitoring + error escalation, never silent
- ▸ Two to three agents across FOH + BOH
- ▸ Per-client dashboard — live action log, outcomes, reviews, cost
- ▸ Monthly tuning + approved playbook revisions
- ▸ The full learning loop + per-contact memory
- ▸ Everything in Growth
- ▸ The full front-of-house + back-office catalog
- ▸ AI voice receptionist — answers, books, escalates
- ▸ Your integrations wired in — calendar, CRM, phone, billing
On the Starter tier we agree on a measurable target up front — a number of staff hours saved or inbound leads recovered in the first 30 days. Miss it, and your setup fee comes back. We can stand behind that because we run the agent ourselves and watch the metric daily — not because we're guessing. Every conversation closes on new money or replaced cost, never on vague "efficiency."
We already run agents like these — on ourselves.
Neuron HQ's own back office runs an inbox-triage agent, a daily-briefing agent, and a workflow optimizer today — the same patterns we deploy for clients. We don't show invented logos or fake testimonials. We show the working system and let you watch yours run in a dashboard.
We lead with dental practices and med spas, where intake pain is acute and a recovered lead is worth real money, and we also serve real estate and law. We can often build a short demo on your own public information first — so you see an agent working before you commit to anything.
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1Map the one painful taskA short call. We pick the single task that loses the most leads or hours, and agree the outcome we'll guarantee.
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2Build, wire, and superviseWe write the playbook, connect the tools, and launch in a supervised mode where every action is human-approved first.
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3Go autonomous, with a netAs accuracy proves out, the agent runs unattended — still escalating edge cases to a human, never failing silently.
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4Tune monthly, expandWe review the dashboard, approve the evaluator's revisions, and add the next agent once the first has earned it.
Questions, honestly answered.
Every answer is visible on the page — no accordions to fight. More across the whole studio lives on the full FAQ.
Will an AI agent replace my staff?
No. Our agents do the repetitive, after-hours, and overflow work your team hates — replying in seconds, answering the phone at 9pm, keying invoices. When anything is ambiguous, sensitive, or out of policy, the agent escalates to a human instead of guessing. The goal is to free your people for the work that needs them, not remove them.
How do these agents learn from feedback and errors?
Three honest mechanisms — not model training. First, when you edit or approve a drafted reply or booking, that correction is saved as a reusable example the agent sees next time. Second, a scheduled evaluator reviews real outcomes against your benchmark and proposes versioned playbook revisions you approve before they go live. Third, errors are captured, tighten the guardrails, and escalate to a human.
Is this just fine-tuning a model on my data?
No, and we will not claim it is. Learning here means memory plus few-shot examples from your corrections, an evaluator that proposes playbook revisions, and guardrails that tighten as errors appear. Your data is never used to train a base model. We say this plainly because over-promising self-training AI is exactly how these projects fail in production.
How long does setup take?
A single Starter agent is typically live within one to two weeks. Growth and Full configurations, including the voice receptionist and integrations, take two to four weeks depending on which systems we connect. Setup includes mapping your process, writing the playbook, wiring the tools, and a supervised launch where every action is reviewed before it goes out unattended.
What happens when the agent makes a mistake?
It never fails silently. Low-confidence or out-of-policy situations are escalated to a human with full context, and the error is logged. Recurring errors automatically propose a guardrail update we review. During the supervised launch period, every action is human-approved first, so mistakes are caught before they ever reach a customer.
Which industries do you serve?
We lead with dental practices and med spas, where lead value is high and intake pain is acute, and we also serve real estate brokerages and law firms. The agents are not industry-specific software — they are configured around your exact process, so the same catalog adapts to any appointment-driven, lead-driven local business.
How is this different from a $20 chatbot or a DIY automation?
A cheap bot is handed to you and breaks the first time reality deviates from the script. We build, host, monitor, and tune the agents on our own infrastructure, with a human-in-the-loop review queue and a monthly learning loop. You are buying a managed, improving service tied to an outcome number — not a one-time handoff that quietly stops working.
What does it cost?
Three tiers, all in USD. Starter is $1,000 setup plus $500/mo for one outcome-guaranteed agent. Growth is $2,000 setup plus $1,000/mo for two to three agents with the dashboard and monthly tuning. Full is $3,000 setup plus $1,500/mo for the complete front-desk and back-office suite including the AI voice receptionist. No long contracts.
What is the outcome guarantee on the Starter tier?
Before we start, we agree on a measurable target for your one agent — for example, a set number of staff hours saved or inbound leads recovered in the first 30 days. If the agent does not hit that number in month one, you get your setup fee back. We can offer this because we run the agent ourselves and watch the metric, not because we are guessing.
How does the AI voice receptionist work?
The voice receptionist, included in the Full tier, answers your phone in a natural voice, handles common questions, books appointments directly into your calendar, and escalates anything it should not handle to a human. It runs on the same tool layer as the text agents, so a call and a web lead are handled with the same logic and the same memory of your business.
Voice agent or text agent — which should I start with?
Most practices start with a text agent because it is the fastest to prove and the easiest to supervise: the Speed-to-Lead Responder or Missed-Call Text-Back recovers revenue you can measure in week one. The voice receptionist is the bigger lift and the bigger replacement of cost, so it usually comes once a text agent has earned trust, in the Growth or Full tier.
Is my data secure and isolated from other clients?
Yes. Every client's data lives in its own isolated, tenant-scoped store, and authorization is enforced on the server for every single agent action — never trusted from the browser. Each agent can only call the specific tools it is granted, with per-client spending caps. We run the platform through an enterprise security audit before any real client data flows through it.
Do the agents work with the tools I already use?
That is the point. The agents act through tools we wire to your stack — your calendar, your CRM or our built-in one, your email, your phone line, and your invoicing. We map your existing process first and connect the systems you already run, so the agents fit into how you work instead of forcing you onto a new platform.
Can I see what the agents are doing?
Yes. Growth and Full include a per-client dashboard with a live action log, the outcomes each agent produced, the items waiting for your review, the playbook revisions the evaluator has proposed, and the running cost. You are never in the dark about what the agents did, what they escalated, or how they are improving over time.
How much of my time does this take each week?
Less every week, by design. Early on you review the agent's drafts and approve corrections, which is what teaches it; that review time shrinks as accuracy climbs. After launch, most clients spend a few minutes a week approving proposed revisions and reading the dashboard. We do the monitoring, tuning, and maintenance for you — that is the managed part.
Can I cancel, and do I keep anything?
There are no long-term contracts; the monthly is month-to-month and you can cancel anytime. The agents run on our managed infrastructure, so cancelling stops the service. Your underlying business data — contacts, conversations, and bookings — is yours and is exported to you on request. We will never hold your customer data hostage.
How do I know it is actually saving money and not just busywork?
We tie every engagement to new money or replaced cost, not vague efficiency. The dashboard reports leads recovered, appointments booked, hours of staff time returned, and calls answered after hours. You can also use the calculator on this page to estimate your own payback before you talk to us — most single-agent setups pay for themselves well inside the first month.
Why a managed service instead of buying software?
Because the failure rate of self-installed AI agents is brutal in the real world — they are sold as set-and-forget and quietly break. A managed service means a real team owns the outcome: we watch the metric, catch the errors, approve the improvements, and tune the playbook every month. You get the result without becoming an AI operations department yourself.
How do I get started?
Tell us your business and the one task that wastes the most time or loses the most leads. We will reply with the right agent, the fixed setup price, the monthly, and the outcome we will guarantee for it. We can often build a short demo on your own public information first, so you see it working before you commit to a pilot.
Tell us the one task you'd hand off first.
Two sentences is enough: what your business does, and the task that loses the most leads or burns the most hours. We'll reply with the right agent, the fixed price, the monthly, and the outcome we'll guarantee.
No drip campaign, no discovery-call gauntlet. A real reply from the people who'll build and run it — usually within one business day. Prefer to talk? Call or text (385) 374-9295.