Forward Deployed AI Engineering

AI Agents & Agentic Workflows That Ship

One engineer builds agents that work inside your existing tools, not a chatbot demo that never touches production.

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Sounds familiar?

01Leads sit unanswered for hours while your team is busy.
02Reporting is manual, so nobody trusts the numbers.
03AI pilots stay in a sandbox and never touch production.

Most "AI agent" pilots stall in a sandbox: a chatbot demo that never gets near the CRM, the inbox or a live customer. The team loses months and the queue keeps growing by hand.

We build agents that sit inside tools you already run — HubSpot, Salesforce, WhatsApp Business API, Google Workspace — and take defined actions: qualify a lead, draft a reply, update a record, flag an exception. Every agent has a human owner and a visible log. Most run on the Claude API or OpenAI, orchestrated with n8n, so the logic stays visible and editable by your team.

What you keep

Working agents live inside your CRM and inbox
Documented rules for what each agent may do
Approval and escalation workflow for edge cases
Activity log and weekly performance summary
Confidence thresholds and escalation rules, documented
Admin access and a runbook per agent

Who this is for

You get inbound volume no one has time to triage by hand.
You want AI touching real records, not a chatbot on a landing page.
You need one accountable owner, not a platform to configure yourself.

Forward Deployed AI Engineering

What we build and run

Design agent scope: what it decides alone, what it drafts, what it never touches.
Build qualification agents that score and route inbound leads automatically.
Build drafting agents that prepare replies and follow-ups for approval.
Connect agents to your CRM, inbox and WhatsApp Business API.
Add guardrails, logging and a human owner for every action.
Set confidence thresholds so an agent escalates instead of guessing.
Test agents against real historical cases before go-live.

How it runs

From kickoff to a running sales system in 30 days.

Week 1-2
Map the workflow and define agent scope and limits.
Week 3-4
Build and connect agents to CRM, inbox and channels.
Week 5-8
Pilot with real cases, tune, then hand over with training.
After
Optional monthly tuning as volume and workflows change.

Questions we get

What can an AI agent safely do without a human?

It depends on the risk of the action, not the technology. We typically let agents draft, score, tag and route without approval, and require a human sign-off on anything that sends money, commits the company or leaves the customer's inbox. We set that line with you before build starts.

Which tools do the agents connect to?

Whatever you already run: HubSpot, Salesforce, Attio or Pipedrive for CRM, WhatsApp Business API and Google Workspace for communication, and n8n or the Claude API underneath for logic and orchestration. We rarely introduce a new platform just for the agent.

How do you prevent an agent from making a costly mistake?

Every agent runs against real historical cases before it goes live, has explicit limits on what it may decide alone, and logs every action it takes. Exceptions and anything outside its limits route to a named person, not a dead end.

How long until the first agent is live?

A first agent, such as lead qualification or reply drafting, is typically live within three to four weeks. Larger agentic workflows spanning several steps run as a six to eight week deployment.

Other sub-areas in this service

AI Agents & Agentic Workflows CRM Implementation Workflow Automation Websites & Landing Pages Mobile Apps Reporting & Dashboards AI Efficiency Audit