Professional Services
AI Agents for Professional Services
Quick answer
Agencies, consultancies and firms lose billable time to intake, scheduling and admin. AgentMesh builds AI agents that triage inquiries, book meetings, and prep the busywork so your experts stay on client work.
What slows Professional Services teams down
- Inbound leads sit unqualified and go cold
- Scheduling back-and-forth wastes senior time
- Repetitive research and document prep before every engagement
A starting agent team
| Agent | What it does | Tools to enable |
|---|---|---|
| Intake Agent | Qualifies inbound inquiries and routes them with a summary | None required · slack_message, send_email or telegram_message to route |
| Scheduler | Proposes and books meetings via Google Calendar | google_calendar_list_events and google_calendar_create_event (OAuth) |
| Prep Agent | Gathers context and drafts briefs ahead of client calls | http_request to your CRM or notes · notion_create_page if the brief lives there |
This team ships as a ready-made setup for Professional Services — install it and you have the three agents above and the workflows between them, then edit each one's instructions.
What a run like this costs
Runs are billed in tokens, so the price follows the size of the job. Every figure below is measured on this product, and all three are the same shape of work as the agents above — one agent reading something, deciding, and calling a tool:
- A support ticket triaged and answered (worked example) — 8.4 seconds, $0.0144
- The same job, escalated to a human as well — 28.5 seconds, $0.0204
- One that failed on its first tool call — 4.1 seconds, $0.0024
Those are measured on a support workload, not a professional services one, so treat them as the order of magnitude rather than your number: cents per job, not dollars. Source: three runs opened up step by step, readable without an account. The free plan gives you 100 runs or $0.50 of usage a day, whichever comes first — enough to measure your own.
Where this goes wrong in professional services
It answers from data it never read
The failure to plan for. Source: a logged run of mine finished COMPLETED after two lookups returned HTTP 403 with "ok": true in the tool result — so the agent believed it had the data, and told the customer it had checked. Read the tool result's status, not the run's.
It runs for weeks and does nothing
A condition that can never match skips its branch and the run still reports success. Have the run report how many items it processed and compare that against what the source handed over. A count of zero on a normally busy morning is a signal; a green status is not.
Nobody looks at it
The honest rule: if nobody would notice the agent being wrong for a month, do not automate that job yet. Start with the one where somebody notices the same day, and keep a person on anything that sends, pays or cancels.
Frequently asked questions
Can agents hand off to each other?
Yes — AgentMesh orchestrates multi-agent workflows (sequential, parallel, conditional, fan-out, DAG) with structured hand-offs between agents.
Is our data isolated?
Yes — tenant isolation, encryption at rest, signed JWT auth and rate limiting; you can bring and rotate your own LLM keys.
Build your Professional Services agent team — free to start
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