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Demonstration board — your operation PNL SL-003 · Date —
Customer supportAgent — running
Lead qualificationAgent — running
Document processingAgent — running
Internal knowledgeAgent — running
Reporting & opsAgent — running
Back-office automationManual — unacknowledged
Unityour business Operatoryou Scheduledyesterday Shiftcontinuous

Your competitors are automating. Are you?

We build AI agents that do real work — and cut through the hype to show you exactly where AI pays off in your business.

One operator can only watch so many boards. Agents watch thousands, unattended. That's the point. —SL
Panel 02 · What we do

Agents that work. Advice that's straight.

Unit 01

AI agents, built for you

Custom agents that answer customers, qualify leads, process documents and clear back-office work — plugged into the tools you already use.

  • Customer support & sales agents
  • Workflow & document automation
  • Deployed, monitored and maintained by us
Unit 02

AI consultancy

No hype, no jargon. We audit your operations, find the highest-ROI opportunities and hand you a plan you can act on immediately.

  • AI opportunity audit
  • Strategy & roadmap
  • Team training & adoption
If AI won't pay off here, we'll say so. —SL
Panel 03 · Use cases

Where agents earn their keep

Customer supportAgent — on shift

Agents that resolve tickets, answer product questions and hand off to humans only when it matters.

Lead qualificationAgent — instant

Instant follow-up on every enquiry — qualified, scored and booked into your calendar.

Document processingAgent — hands-free

Invoices, contracts and forms read, extracted and filed without anyone touching a keyboard.

Internal knowledgeAgent — on call

One agent that knows your docs, policies and systems — answers your team instantly.

Reporting & opsAgent — daily

Daily numbers pulled, reconciled and summarised before your first coffee.

Back-office automationAgent — unattended

Repetitive admin — data entry, scheduling, chasing — done by agents, not your staff.

Panel 04 · Sequence of operations

From first call to running agents

01 · Audit Initiated

A free session on your operations. We find where AI saves the most time and money.

02 · Plan Scoped

A concrete roadmap with scope, cost and expected ROI — no vague promises.

03 · Build In work

We build and integrate your first agent, tested against real work, in weeks not months.

04 · Run In service

We monitor, maintain and keep improving — you see the results in your numbers.

In service — continuous

SevernLabs — we design, build, deploy and maintain everything ourselves. Our own agents run in production around the clock, on infrastructure we operate — the same discipline your agents get.

Panel 05 · Sample builds

Three boards, exactly as wired

Real canvases from real builds — two agents from our own product, one workflow built for a client. This is what the work looks like.

The music-generation agent behind Soundlab AI (CreateMusic.net), exactly as it runs in production: a webhook feeds the agent, chat memory sits in Postgres, retrieval covers the product docs, and tools generate music, look up accounts and tasks, and check server status.

n8n workflow canvas: a webhook-driven AI Agent node wired to an OpenAI chat model, Postgres chat memory, a soundlab_docs vector store with OpenAI embeddings, and tools for music generation, user accounts, tasks and server status, ending in a webhook response.
Monitor 01 · Soundlab AI — in service

The email agent on the same product's support inbox. Mail arrives over IMAP, spam is filtered out, and the agent answers customer queries from the product docs — sending the reply and filing the thread as handled. Anything it isn't sure about goes to a needs-review folder and a human is notified for review.

n8n workflow canvas: an IMAP trigger feeds a spam filter, then an AI Agent node wired to an OpenAI chat model and two soundlab_docs vector-store tools; a Switch routes the result to format-and-send email and move to handled, to a needs-review folder with a Discord notification, or to spam.
Monitor 02 · Soundlab AI email desk

Built for a client: a video-production pipeline that scripts the idea, voices it, generates and animates the imagery, assembles the cut with FFmpeg, optimises the output and cleans up after itself. A task that took two hours by hand now runs in about ten minutes.

n8n workflow canvas of a large video-production pipeline: a webhook trigger with guardrails leads to LLM idea and script generation, text-to-speech, image-prompt creation, image generation and animation via external APIs with polling and retries, audio and animation merging, FFmpeg video assembly, output optimisation and file cleanup.
Monitor 03 · Client build2-hour task — now ~10 minutes
Panel 06 · Operator's manual

Questions we hear a lot

Most first agents ship in 2–4 weeks. We start with the highest-value workflow, get it live, then expand from there.

No. We design, build, deploy and maintain everything. Your team just uses the results — we handle the plumbing.

Consultancy engagements start with a fixed-price audit. Agent builds are scoped per project, so you know the number before we start.

Yes. We work within your infrastructure and compliance requirements, and we never train models on your data.

We'll tell you. The audit is honest — if a spreadsheet or a simple script beats an agent, that's what we recommend.

We mean that last one. —SL
Panel 07 · Work request

Tell us what's slowing you down.

Book a free AI audit. We'll look at your operations and show you exactly where agents can save time and money — no obligation, no sales script.

Log a work request below and press the acknowledge button — four fields and a note is all it takes.

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