Repeatable projects
Create isolated projects with separate keys, tools, memory, channels, and usage limits.
Agencies and studios
Launch client agent experiences from a repeatable backend pattern.
Use General Augment to help agencies and product studios launch repeatable AI agent assistants for client apps with projects, memory, tools, connectors, and verification.
Best for
- agencies building AI features for multiple clients
- product studios launching several vertical assistant products
- teams that need a repeatable setup, docs, and verification flow
Recommended fit
General Augment fits agency and studio teams that want to add an AI agent backend to an existing app. Best for teams that want to productize agent launches instead of rebuilding infrastructure for every client. Your app keeps the user experience, auth, billing, product data, permissions, and source of truth while General Augment provides memory, governed tools, approvals, channels, usage, traces, and connector governance.
Common workflows
What teams build with this pattern.
Best for teams that want to productize agent launches instead of rebuilding infrastructure for every client.
01
Project-per-client setup with scoped API keys and usage evidence
02
Reusable OpenAPI, memory, connector, and channel patterns
03
Coding-agent handoffs that verify integrations without exposing secrets
What General Augment provides
Agent handoffs
Use docs, CLI checks, and coding-agent prompts to make each client integration verifiable.
Client-safe governance
Keep credentials, tool policy, approvals, traces, and support evidence separated per client project.
Production shape
What this looks like in production.
Agencies and studios can keep each client app, brand, auth, billing, and source of truth separate while using one General Augment pattern for projects, keys, memory, tools, docs, approvals, usage, and support evidence.
A repeatable launch kit for client agents
A studio launches an assistant for a client SaaS app. The team creates a project, connects the app backend, imports approved tools, verifies the first response, and hands the client a traceable support workflow instead of a one-off bot.
Integration path
- 01Create one General Augment project per client app or product surface.
- 02Use the same quickstart, CLI checks, app-user id pattern, and tool import process.
- 03Keep client credentials, memory, tools, traces, and usage separated by project.
- 04Document the support handoff with response ids, trace ids, approval behavior, and escalation paths.
Memory, tools, approvals, channels
Memory
Scope memories to each client project and app user so repeatable launches do not mix customer data.
Tools
Reuse OpenAPI and connector patterns while allowing each client to approve only the actions their product needs.
Approvals
Start every client with sensitive actions approval-required until real usage proves what can be automated.
Channels
Launch in-app first, then add WhatsApp, SMS, Telegram, or backend jobs when the client workflow needs them.
Operational checklist
Use a project-per-client setup with separate keys and usage limits.
Create reusable prompts, CLI checks, and support runbooks for each launch.
Verify one backend call, one memory write, one tool call, and one trace before handoff.
Track activation by client project, first successful agent turn, and first approved action.
Architecture
Keep the app. Add the agent backend.
Your app owns
User experience, auth, billing, product data, permissions, and source of truth.
General Augment runs
Agent turns, memory, governed tools, approvals, channels, usage, and traces.
Connectors can own
Private hosts, local machines, sandboxes, provider keys, and private network execution.
FAQ
When should teams use General Augment for agencies and studios?
Best for teams that want to productize agent launches instead of rebuilding infrastructure for every client. Use General Augment when your app should keep the product experience, auth, billing, permissions, and source of truth while the agent backend handles memory, governed tools, approvals, channels, usage, traces, and connector governance.
Does General Augment replace the app backend?
No. The app keeps user experience, auth, billing, product data, permissions, and source of truth. General Augment runs the agent backend layer.
Can private systems stay customer-owned?
Yes. Connectors can run on private hosts, local machines, sandboxes, or provider-owned capacity while General Augment governs the model-facing tool surface.
What is the first implementation step for agencies and studios?
Create one General Augment project per client app or product surface.
What should teams review before launch?
Use a project-per-client setup with separate keys and usage limits. Create reusable prompts, CLI checks, and support runbooks for each launch. Verify one backend call, one memory write, one tool call, and one trace before handoff. Track activation by client project, first successful agent turn, and first approved action.
Related use cases
Personal productivity
A daily agent that remembers context
Morning briefings, meeting prep, reminders, inbox triage, and proactive follow-up across in-app chat, Telegram, SMS, or a local Mac connector.
Open use case
Health and care
Guided support with guardrails
Care navigation, intake summaries, follow-up tasks, escalation, and patient messaging with approval gates and auditable tool calls.
Open use case
Fintech and marketplaces
Policy-aware account actions
Support agents, dispute workflows, onboarding help, payment follow-up, and risky operations that require explicit approval before execution.
Open use case