MAIDA / PAIDA
One AI workforce. Two ways to run it.
Run your new AI workforce either through a managed service — MAIDA, we run everything for you — or done with you on your own private AI operating system, PAIDA. Same agents, same private container, same human approval gates. You choose who drives.
We run the whole system. You approve the work.
MAIDA — Managed Artificial Intelligence Digital Agents — is the complete agent team, coordinated for you and tuned by a human operator. Custom agents built around your data, workflows, approvals, reporting cadence, and commercial outcomes. Not a self-serve chatbot. Not a generic automation pack.
We run and maintain everything in a private, secured container that is yours alone. A human operator reviews every morning. You approve the work — on WhatsApp, by default. Outcomes, not setup.
The whole platform, in your hands.
PAIDA — the platform counterpart to MAIDA — gives you your own private, secured AI operating system with a team of ready-to-run agents. You drive, you stay autonomous, and the superpowers are one click away whenever you need them.
Your private container, managed for you. Ready-to-run agents, yours to shape. Connect your own models — full control, no lock-in. Superpowers on demand with flexible pay-per-use credits, and the AI Jungle team beside you when you want help.
MAIDA / PAIDA operating contract
One AI workforce, two operating modes: managed for you, or done with you.
The site states this explicitly so humans, Google generative search, and browser agents can retrieve the same answer without guessing from design.
- Service
- MAIDA: the AI workforce run by AI Jungle as a managed service. PAIDA: the same workforce delivered as your own private AI operating system, done with you.
- For
- Founder-led boutique consulting and service firms where senior time is trapped in coordination overhead.
- Outcome
- An operating AI workforce: recurring-work audit, named agents with one job each, approval gates, and measurable operating loops.
- Inputs
- Meetings, documents, workflows, decisions, approvals, rejected drafts, and business outcomes.
- Human approval
- Draft autonomously; ship external, financial, sensitive, or production actions with permission.
- Learning
- Client-specific learning stays isolated; de-identified patterns improve AI Jungle playbooks.
Client loop. The client agent improves from usage, corrections, approvals, rejected drafts, decisions, and business outcomes inside that client's isolated context.
AI Jungle loop. Patterns across deployments improve AIJ templates, prompts, dashboards, operating procedures, and quality gates without leaking client data.
Managed loop. AI Jungle keeps the system running, measured, and corrected. The value is not the model. The value is the operating cadence around it.
Every deployment draws from the same roster — meet the full team. These are the roles with their own deep-dive pages today.
Baibot
Coordinator and Chief of Staff Agent
Open page →Bob
Business Opportunity Builder Agent
Open page →Eva
Executive Operations Assistant
Open page →Hipo
Marketing and Visibility Agent
Open page →Moni
Money Operations Agent
Open page →Memo
Company Brain and Memory Agent
Open page →Nestor
Speed-to-Lead and Reception Agent
Open page →Goria
QA and Security Agent
Open page →CBO
Chief Brand Officer Agent
Open page →Jimmy
Builder Agent
Open page →SoFI
Signals and Feed Intelligence Agent
Open page →Sensei
Learning Companion Agent
Open page →