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AI for talent agencies.

Deal discovery, talent-to-brand matching, intel, and deal lifecycle automation. We are the implementation layer between your roster and your pipeline, and we build on Claude, Clay, Tavily and HubSpot.

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18K+ deals processed 14 staff trained, 4 regions Mutual NDA in 24h

What does AI implementation look like for a talent agency?

Two layers. Layer one is deal flow: discovery agents that surface brand opportunities, enrichment from Clay and Tavily, and matching logic that ranks talent against briefs. Layer two is the deal lifecycle: outreach drafters with talent voice profiles, agreement checkers, rate engines pulled live from your CRM, and reporting for both managers and talent. We build both layers inside your existing HubSpot, Slack and Claude, then train the team to own them.

The numbers that move the conversation

18K+
deals processed in our live talent build

Brisbane talent agency, 5 pipelines, 14 staff. Full deal economics, CPM tracking and revenue attribution running through one Claude + HubSpot stack.

6
production Claude agents in deployment

Discovery, matching, intel, outreach, deal lifecycle, reporting. Each agent plugs into Clay, Tavily, HubSpot and the YouTube API.

AI consultant vs in-house AI hire vs doing nothing

The three real options for an agency principal. We are direct because the comparison matters.

DimensionAI consultant (THL)In-house AI hireNothing
CostA$2,000 a month, with builds quoted per phaseA senior salary plus on-costs$0 (apparent)
Speed to first agent liveWeek 2 to 3Month 4 to 6Never
Ongoing riskWe rotate out cleanlySingle point of failureLosing briefs to faster agencies
Knowledge retentionDocumented playbook staysWalks out the doorNone to retain
Talent & brand dataStays inside your HubSpotOften vendor-shapedSitting in spreadsheets

How a talent-agency engagement runs

Discovery
Week 1

NDA signed. We map every pipeline: discovery, matching, outreach, deal lifecycle, reporting. Audit your stack (HubSpot, Slack, doc storage, contracts).

Foundation
Weeks 2 to 4

Claude Workspace stood up. Prompt library and skills deployed. Email drafter with talent voice profiles. Agreement checker. Rate engine wired to your CRM.

Agentic stack
Weeks 4 to 8

Six Claude agents plugged into Clay, Tavily, HubSpot and YouTube API. They automate discovery, matching, intel, outreach, deal lifecycle and reporting.

Train & retain
Ongoing

Every team member trained to build agents and write skills. We stay on as fractional AI ops and update the playbook quarterly as the platforms evolve.

What an engagement looks like

Drawn from our live Brisbane talent-agency engagement. The full case study sits on the homepage.

DEPLOYED Talent agency, Brisbane: 18K+ deals, 5 pipelines, 14 staff trained
What we built
Claude Workspace
Cowork, Dispatch, Channels. Slack integrations. Every team member trained to build agents and set up skills.
Prompt Library
Custom skills deployed into Cowork/Code. Email drafter with talent voice profiles. Agreement checker. Rate engine pulling live from CRM.
Agentic Stack
Six Claude agents plugged into Clay, Tavily, HubSpot, YouTube API. They automate discovery, matching and intel.
Stack deployed
Claude
Cowork + Code. Skills, agents, prompt library. The team's daily driver.
Clay + Tavily
Brand enrichment, competitive intel, audience research. All piped into HubSpot.
Slack + HubSpot
Deal notifications, agent outputs, team coordination. Single source of truth.

See the full 32-section case study →

Common questions from agency principals and ops leads

What does AI implementation look like for a talent agency?

Two layers. Layer one is deal flow: discovery, enrichment and matching. Layer two is the deal lifecycle: outreach drafting, agreement checks, rate logic and reporting. We build both inside your HubSpot, Slack and Claude, then train your team to own them.

Do you sign NDAs and protect talent and brand data?

Yes. Mutual NDA before we touch a roster or brief. We build inside your own stack (HubSpot, Slack, Google Workspace), so you control the tenant. We never train external models on agency data.

How is this different from hiring an internal ops or AI lead?

An internal AI lead costs a senior salary plus on-costs and takes months to hire. We scope and quote each phase before it starts, then the fractional deployed engineer runs it at A$2,000 a month + GST.

Will you train our talent managers and ops team on the systems you build?

Every engagement includes hands-on training. Our current live build has 14 staff trained across four regions, and every team member can run agents, write skills, and extend the prompt library. We do not leave systems behind that only the founder can operate.

Where does the data live?

AU-region by default (Google Workspace AU, HubSpot AU instance, AWS Sydney for custom storage). Talent rosters, briefs, contracts and deal economics stay inside your existing tools. Every system is built so a vendor swap is a config change, not a rebuild.

Adjacent reading

The live talent-agency engagement

The full 32-section case study covers 18K+ deals, 5 pipelines, 6 production agents and 14 staff trained across four regions.

See the engagement →

AI Ownership Readiness Check

Six questions, scored instantly in your browser. Use it with your ops lead before a kickoff call.

Take the check →

State of AI Readiness: Australian SMB 2026

First-party survey of 54 Australian SMBs. The base rate for where most agencies actually sit.

Download the report →

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