A person approves what matters
Agents draft, sort and update. Customer emails, anything that moves money and anything in a regulated context wait for a named person to approve, and every approval is logged.
Custom AI Agents & Workflows Your tools talk to each other. Your team stops copy-pasting.
When no ready-made app fits, we build AI agents and workflows that connect the tools you already pay for. They follow your rules, ask a person before anything important goes out, and run documented and monitored in your own accounts.
Free · 20 minutes · You talk to Syed · Scoped before anything is built
How it runs
Custom AI Agents Running
Every run is logged
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Something happens in one tool
A call ends, a form arrives, a deal changes stage or a file lands in a folder.
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The agent reads and decides
It summarizes, pulls out the fields that matter and applies your rules. A person approves where it counts.
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Your other tools update
CRM, project tool, accounting and team chat updated through their APIs, with no copy-paste.
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Every run is logged
Each success or failure is recorded, and errors alert a named person straight away.
See it work
Watch it handle one.
A scripted walk-through of a typical custom ai agents conversation — press play.
Simulated demo
Sales call to CRM, tasks and follow-up
Ridgeway Digital · after-call workflow n8n · run #212 · Wed 2:38 pm
- Event
Zoom call ended · “Kestrel Home Renovations · website rebuild, discovery” · 34 min · transcript ready (recording notice given at the start)
- Summarizing the transcript… Summary written · 3 decisions · 5 action items · timeline and decision-maker captured n8n · AI Agent
- Pulled from the call
- 12-page rebuild
- Decision-maker: Hannah, owner
- Wants an online quote form
- Start early November
- Proposal due Friday
- Updating the deal in HubSpot… Deal moved to Proposal · next step and close date set · summary logged on Hannah’s contact HubSpot
- Draft follow-up · to Hannah Lee Needs approval
- Subject
- Recap and next steps: your website rebuild
- Covers
- 3 decisions, 2 things we need from you, proposal by Fri
- Sends from
- Marco’s Gmail, only after approval
- AI agent
Recap for Hannah is in your Gmail drafts. It confirms the 12-page scope, the quote form and a proposal by Friday. Send as is, or edit first?
- Marco · account lead, in Slack
Changed the start date to Nov 10. Approved, send it.
- Sending the approved email… Sent from Marco’s Gmail at 2:41 pm · copy logged on the HubSpot deal Gmail
- Creating tasks in the project… 5 tasks in “Kestrel · proposal” · owners and due dates taken from the call Asana
- Posting the summary and logging the run… #sales updated · run #212 logged · 4 tools, 0 errors Slack
- Event
Kestrel moved to Proposal · 5 tasks assigned · proposal due Fri · if any step had failed, Marco would have been alerted in Slack
Call to CRM, tasks and Slack in 2 min 50 s. The email went only after Marco approved it.
Set this up for my business What it replaces
Off your plate.
- Retyping the same customer details into three different tools
- Writing up notes, CRM updates and tasks after every call
- Reading every job application just to see who meets the basics
- Automations nobody remembers building, failing quietly
How it works
Step by step.
- 01
We map the hand-offs
We list every place your team moves data by hand: what triggers it, which tools it touches, how often and the usual exceptions. Then we rank the list by hours saved and risk.
- 02
We design it with approval points
We choose n8n, Make, Zapier or plain code for each job, give the agent only the access it needs, and mark the steps where a person approves: anything sent to a customer, anything involving money and every hiring decision.
- 03
We test on your real past data
Before it goes live, the workflow runs against last month’s calls, forms or records. You see what it would have done, and we measure how often it matched your team.
- 04
It runs, monitored, and it’s yours
Every run is logged, failures trigger an alert, and each workflow comes with plain-English documentation. It all lives in accounts you own.
Works with the tools you already use
- n8n (cloud or self-hosted)
- Make
- Zapier
- MCP connectors
- HubSpot
- GoHighLevel
- QuickBooks Online
- Xero
- Jobber
- Clio
- Shopify
- Asana
- Google Workspace
- Slack
- Zoom, Google Meet and Teams notes
Connected through official APIs where available. Names and logos are trademarks of their owners; no affiliation implied.
Guardrails
You stay in control.
Least access, full audit trail
Each workflow gets only the permissions it needs, read-only where that’s enough. Credentials stay in your accounts, and every run records what it changed and who approved it.
Recording and privacy, handled up front
Calls are transcribed only after participants hear a recording notice. We keep only the data each workflow needs and design around PIPEDA, with n8n self-hosted in Canada if you prefer. For Ontario clinics we act as an agent of the custodian under PHIPA; for US practices we work in line with HIPAA.
In hiring, a person decides
A screening agent summarizes applications against your criteria and books interviews, but never rejects anyone. Ontario employers with 25 or more employees must disclose AI screening in job postings, and we check local US rules, such as New York City’s, first.
Where it fits
Where it fits best.
Professional Services Meeting notes into CRM tasks, and new engagements set up across practice, billing and document tools. See professional plays Trades & Home Services Won quotes become jobs and materials orders, and finished jobs flow into invoicing without retyping. See trades plays Real Estate & Mortgage Leads from portals, ads and your website merged into one CRM record, with deal stages kept in sync. See real estate plays Health, Dental & Med Spa Admin hand-offs like supply reorders and referral tracking, kept apart from clinical records. See clinics plays
In practice
What it looks like.
A nine-person web and marketing agency
Two account leads run about 8 sales and client calls a week, then write notes, update HubSpot and set up tasks by hand. The office manager copies new clients, won deals and approved hours between HubSpot, Asana and QuickBooks Online.
About 2.5–3.5 hours a week back for the account leads and office manager (estimate)
The math
- After-call admin: 8 calls/week × ~15 min saved on notes, CRM updates and tasks (a short review of the draft email stays) ≈ 120 min/week
- Copy-paste hand-offs: ~25 a week between HubSpot, Asana and QuickBooks × ~4 min each ≈ 100 min/week
- Total ≈ 220 min/week ≈ 3.7 h/week
- Less 20% for overlap and ramp-up ≈ 2.9 h/week
Estimates use typical volumes and include a 20% allowance for overlap and ramp-up. Your audit measures the real numbers.
Why it matters
When your team is the glue between your tools
Most small businesses run on five to ten apps that each do one job well. The trouble is the gaps between them. A call ends and someone writes the notes, updates the deal and sets up the tasks. A client signs and someone copies the details into three systems. An application arrives and someone reads it just to see whether it meets the basics.
Ready-made integrations cover some of this. They usually stop at the step that needs judgement, like deciding what a call actually agreed or which deal a document belongs to. That step is where people end up copying and pasting.
What custom AI agents change
An agent handles the judgement step under rules you write down. It reads the transcript, the form or the email, pulls out what matters, and updates the tools on either side. In the sample above, a sales call becomes a CRM update, a drafted follow-up, assigned tasks and a Slack summary. The email waits for the account lead to approve it.
The same pattern covers meeting notes into CRM tasks, applications summarized for a hiring manager, data kept in sync between tools, and MCP connectors that let an AI assistant work inside your systems with limits you set. For a single job, one of our ready-made solutions may fit better. Lead qualification handles new enquiries, and client onboarding handles intake.
Built to be owned, not rented
Automations nobody understands become a liability. Each workflow comes with documentation that says what it does, what it can touch and who gets alerted when it fails. It runs in accounts you own, and errors reach a person within minutes instead of surfacing weeks later. We start with the one or two hand-offs that cost you the most time each week, run them alongside your team until the results match, then move on to the next.
How we roll it out
Audit. Build. Run.
Every engagement is scoped on a call. You’ll know the cost before anything is built.
- 01
Audit
- Hand-off map: every place data is typed twice, with volume and time per week
- Shortlist ranked by hours saved and risk, with approval points marked
- Platform recommendation for each job: n8n, Make, Zapier or code, and why
- 02
Build
- Agents and workflows built in your accounts and tested on real past data
- Error alerts, automatic retries and a run log switched on
- Plain-English documentation: what each workflow does, its access and its owner
- 03
Run & Optimize
- Monitoring, with fixes when an app changes its API
- Monthly review of failures, exceptions and the next hand-offs worth automating
- Short monthly report: runs, errors, approvals and estimated hours saved
FAQ
Questions owners ask about Custom AI Agents
Last updated October 7, 2026
Should our workflows run in n8n, Make or Zapier?
It depends on the job. Zapier suits simple, low-volume hand-offs, Make suits visual workflows with a few branches, and n8n suits higher volumes, AI agents and data kept on your own server. When none fits, we write a little code.
Can our team take the custom agents and workflows in-house later?
Yes, because you own them from day one. They’re built in accounts in your name, with your credentials and our documentation, so nothing is locked to us when you bring the work in-house.
What happens when a workflow fails or an app changes its API?
A failure alerts a named person by Slack or email, and the failed item is held in a queue rather than lost, ready to replay once fixed. Watching for API changes is part of the monthly running plan.
Can an AI agent screen job applications for us?
It can summarize each application against your criteria, flag missing information and book interviews. A person reviews the shortlist and makes every decision. We also help you add the AI-use notices your job postings may need.
What is an MCP connector, and when is one worth building?
MCP, the Model Context Protocol, is an open standard that lets AI assistants such as Claude use your business tools with permissions you set. It’s worth it when your team already works in an AI assistant and wants it to look up a client or create a task. We start read-only and log every action.
What do custom AI agents cost to build and run?
It depends on how many tools are involved, the volume of runs and how many approval steps the workflow needs. We scope it on a short call and give you a fixed build price and a clear monthly running cost before anything is built.
Pairs well with
Often built alongside.
Let’s map Custom AI Agents to your workflow.
Bring your call volume, your tools and the part that annoys you most. In 20 minutes you’ll know what it would take — and whether it’s worth doing.
Free · 20 minutes · You talk to Syed · Prefer email? muhammad@sadaat.ca