Agents built into the tools you already use.
We build three categories of agent — customer support, sales and lead-qualification, and internal operations — and measure impact in hours saved per week. AI transformation is 10% algorithm, 20% tech backbone, 70% people and process. We do the 70%.
An agent isn't always the answer.
Before you book anything, here's how we judge whether a workflow is a fit. It's the same test we apply in the audit.
A strong fit when
- The work is high-volume and repetitive: the same task, many times a week.
- A person currently does it by following a pattern you could write down.
- It lives in tools an agent can plug into — email, chat, CRM, helpdesk, docs.
- There's a number that tells you it's working: hours saved, response time, leads handled.
Probably not yet when
- Every case genuinely needs human judgment.
- The process changes faster than you could document it.
- The volume is too low for automation to pay back.
- There's no digital trail — the work lives on paper or in people's heads.
Not sure which side you're on? That's exactly what the free audit is for — and we'll tell you honestly if the answer is "not yet."
Three categories of agent.
Customer support agents
Tier-1 support follows patterns. Status checks, password resets, return policies, common how-tos — your team spends hours every week answering the same questions in different wording. An agent learns the patterns, handles the volume, and routes the genuinely tricky cases to a human.
- Inbox triage and auto-response for tier-1 questions across email, chat, and forms
- Smart routing by topic, urgency, and customer segment
- Knowledge-base answers grounded in your real documentation
- Status-check responses pulled from your CRM or order system
Sales & lead-qualification agents
Inbound leads need fast, useful first contact. An agent answers questions in real time, qualifies fit against your criteria, and routes hot prospects to a human while the interest is fresh. Your team spends time on the conversations that actually need a person.
- Real-time response to inbound web-form and chat leads
- Fit qualification against your ideal-customer profile and current capacity
- Question-answering on pricing, scope, and timelines using your real sales materials
- Calendar hand-off to a human rep once a lead is qualified
Internal operations agents
Most operational workflows have a slow step — a document to read, a record to extract, a data field to compare — that bottlenecks the rest. An agent runs that step at the same quality your team would, faster, and at any hour.
- Document processing: invoices, contracts, intake forms, scanned PDFs
- Data extraction and validation from unstructured text into structured fields
- Cross-system workflow orchestration — moving records from one tool to the next under business rules
- Internal-question agents on top of your runbooks, policies, and SOP documents
We'd rather show you than tell you.
We're a new agency, so we won't pad this page with logos. What we can do is show you working things.
Atlas — a live agent
Atlas is a working agent we built. Tell it about a workflow your team spends too much time on, and it'll tell you whether an agent fits — honestly, before you ever book a call.
Talk to AtlasWe also ship product: BotDesk, an AI business assistant for small businesses — built and run by us.
See BotDesk →Four steps, no surprises.
Discover
We sit down with the team that runs the workflow. Watch how it works today, where it breaks down, where the friction lives.
A workflow brief — current process, automation opportunity, rough fit assessment, and a concrete first agent we'd build.
Two days to a week, depending on how many people we need to talk to.
Design
We spec the agent — capabilities, integration points, escalation paths, success metrics. We agree on what "working" means before we build.
A short technical spec your team can review and either approve or push back on. No surprises during build.
A few days. Faster on simpler workflows.
Deploy
We build the agent, integrate it with your tools, and train the team that will work alongside it. We ship to a small pilot before going wide.
A working agent in production, integrated, with a runbook your team can reference. Plus a clear off-switch if anything goes wrong.
Two weeks for a standard pilot; up to three when integrations are complex.
Optimize
We measure impact against the success metrics from Design. We tune what's not working. We expand scope when the foundation is solid.
Weekly metrics review during the first month, monthly after that. Concrete recommendations for what to ship next.
Ongoing if you want — see the engagement models below.
Three ways to work with us.
Two-week pilot
Fixed scope, fixed price. One workflow, fully built and integrated. Designed for first-fit projects where you want concrete proof before committing further.
Multi-month partnership
Multiple workflows over a 3–6 month engagement. Spec a roadmap together, ship one workflow at a time, expand as wins land.
Monthly capacity
Reserved engineering time for ongoing tuning, new agents, and small improvements. For teams already running production agents that benefit from continuous iteration.
Straight answers.
Typically three to four weeks end to end: a free audit (two days to a week), a few days of design, then the two-week pilot build. Integration complexity is the main variable — an agent on one clean system ships faster than one stitched across four. Either way, you'll have a realistic timeline before we start, not after.
We quote after the free audit, because cost tracks integration complexity more than anything else — and we'd rather give you a real number than a misleading range. The two-week pilot is fixed-scope and fixed-price, so you know the full cost before committing to anything. The engagement models above show how each format is priced.
No — that's the point. We build agents into the stack you already run: your helpdesk, your CRM, your inbox, your docs. If a workflow would genuinely be better served by a different tool, we'll say so in the audit. But rip-and-replace is not how we work.
The agent is built against your tools' integration points, so switching a tool means reconnecting that part — not rebuilding the agent. The logic, prompts, and workflows carry over. Re-integration is a small, scoped piece of work, and exactly the kind of thing the monthly capacity model covers.
Your data stays in your systems — agents work through the same permissioned access your team already uses, scoped to the minimum the workflow needs. Where a third-party AI provider processes content, we name it in our privacy policy and work within your data-handling requirements. Nothing about your business is used to train anyone's models, and all of this goes in writing in the engagement agreement.
It will, occasionally — anyone who says otherwise is selling something. So we design for it: the agent escalates to a human when it isn't confident, every action is logged and reviewable, and there's a clear off-switch from day one. During Design we agree exactly what it may do alone and what always goes to a person.
Agents need tending — knowledge bases drift, tools update, edge cases surface. The first month after deploy includes weekly tuning as standard. After that, most teams either run it themselves with the runbook we leave behind, or put a small monthly capacity retainer in place. We'll recommend whichever your situation actually warrants.
You do. The prompts, workflows, configuration, and any custom code from your build are yours, documented in the runbook. If we part ways, you keep a working system. We don't do ransom-model lock-in.
Ready to find your first AI win?
Free workflow audit. No commitment. We'll tell you honestly whether an agent fits.
Or send a message via contact form.