Private GPT for agencies
Your clients trust you with secrets. Does your AI?
Private GPT for agencies: the AI power your team already uses, in a dedicated environment on your domain, with approved client sources, configured access, and documented model-provider terms.
The leak nobody audits.
Right now, someone at your agency is pasting client material into a public AI tool. Embargoed announcements, crisis plans, healthcare client work. Not because they’re careless, because the tools are useful and nobody gave them a safe version.
Banning AI doesn’t stop it. People switch to personal accounts and phones, and the usage you could have seen becomes usage you can’t.
For an agency, this isn’t an IT preference. Confidentiality is the product. One client conversation about where their announcement went costs more than any software ever will.
Same power. Your walls.
Multiple Models, One Platform
Use supported GPT, Claude, Gemini, and open source models through one governed interface.
Remembers Your Accounts
Clients, projects, voice, past decisions, so your team stops re-explaining context.
Reads Your Documents
Briefs, coverage reports, RFPs, contracts, plain-English questions with sourced answers.
Runs Your Workflows
Press release drafting in client voice, coverage summarization, RFP assembly, crisis doc Q&A.
Your Brand, Your Domain
White label: your logo, your colors, ai.youragency.com, a capability you can show your own clients.
Built for how agencies actually work.
The press release, in their voice
Draft a press release in an established client's voice with the client's own approved materials as context.
A week of coverage, client-ready
Summarize a week of coverage into a structured draft your team can review before it reaches the client.
The crisis binder at 11pm
Ask a crisis binder questions at 11pm and get sourced answers instead of a document hunt.
Validate the fit before discussing a deployment
The first conversation stays grounded in evidence you can evaluate for your own agency: the data boundary, one real workflow, and a deployment scope.
Map the data boundary
Identify which client material may enter the assistant, where it lives, and who should be allowed to reach it.
Review a real workflow
Bring one repeatable agency task so the discussion stays grounded in work your team actually performs.
Scope the deployment
Agree on the required controls, connections, users, and support before a timeline or price is proposed.
Start with a working session
We will map one agency workflow, the approved client information it needs, the access and provider boundaries, and the deployment factors that shape timeline and pricing.
Book a meetingPrefer to start lighter? The HummingAgent Brief covers what’s actually working in real businesses, twice a month. Sign up here.
Agency questions, answered
We already have ChatGPT Team, how is this different?
That solves seats, not walls or workflows. One model family, no white label, no client-shaped memory, and personal and work account mixing continues.
What happens to our data?
The application and approved indexes are configured in a dedicated Azure environment. Storage, connected systems, model endpoints, retention terms, training terms, logging, and deletion are documented for the deployment.
How fast is deployment?
The timeline depends on your approved data sources, access model, integrations, and security review. We map those requirements with you before proposing a deployment plan.
What does it cost?
Pricing depends on the team, data sources, controls, integrations, and support involved. Book a meeting and we will talk through the scope before preparing a proposal.
Want the broader picture first? See how deployment works, the security architecture, or private AI for marketing agencies.