Create an AI-Native Service Company Platform
Put your firm’s expertise into an application: agents do the work, your qualified people review and sign, and you can show what happened.
Sell the outcome. Keep the expertise.
> Your method, carried out by agents > Qualified people review and sign > A record of what happened
An AI-native service firm, in law, accounting, brokerage or support, sells finished work rather than seats. Agents carry out the firm’s own method, and the firm’s qualified people review and sign what leaves it.
Wildo is the backbone of that firm’s application. Every agent acts under a named authority, every decision reaches someone entitled to take it, and the firm runs the application on its own infrastructure.
From a request to the proof of what was done
Agents do the work
Agents run inside the application with the firm’s instructions and tools. They can search the firm’s records and documents without seeing more than the person they work for may see, and every change they make is recorded as the agent’s, under the authority it acted for.
A qualified person decides
When an agent reaches a step that needs judgement, the work pauses and the decision goes to the right reviewer: a named person, or anyone holding a role, never the person who asked. The reviewer approves, amends or rejects, and the action then runs with the requester’s rights, not the reviewer’s.
The firm can show what happened
Every action is written to an audit trail that can be sent on to a security team’s SIEM. Data is kept for the periods the firm declares and deleted on schedule.
Example: A bookkeeping firm closing its clients’ months
Each client has its own workspace in the firm’s application. An agent prepares the month-end reconciliation from the client’s records and proposes adjustments for the entries it cannot match. A qualified accountant reviews each proposal, amends what needs amending and approves it. The adjustment is recorded, with the agent that proposed it and the person who approved it.
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- Agents defined with the firm’s instructions, tools and retrieval over its resources and files, always within the caller’s own access.
- Attribution on every audit record: which kind of authority acted, and which agent, conversation and tool did the work. Exported to a SIEM as CEF, LEEF or OCSF.
- Review gates on an agent’s actions, routed to the requester, a named person or a role, with a reviewer inbox, approval with modifications and the requester’s authority checked again at approval.
- Signed inbound webhooks, stored durably, retried in order and replayable by an administrator.
- Retention periods bound to each kind of data, with deletion on schedule on both supported databases.
Landing now
These are built in the framework and are completing their first end-to-end runs in a live application:
- Agents that run on a schedule or when a message arrives, under a machine identity each organization grants, pausing for a reviewer when they reach a gated step.
- Review deadlines, reminders and escalation, counted in business hours against the firm’s calendar.
- Relationships the client controls, which let the firm’s named experts work inside the client’s organization.
- Legal holds, statutory retention inside an erasure request, and a record of every scheduled deletion.
- Incoming messages grouped into threads, with the sender’s assurance level and a declared reply path.
In the next framework release
- Receiving email directly into the application.
- Cost per case: attributing each model call to a client and a case.
- A queryable record of how experts corrected an agent’s work.
- Finer client control over the firm’s experts: approving each expert, delegating named administrative rights, and applying the client’s own sign-in policy.
How it is built with you
The firm’s experts bring the method: the criteria, the decision points and who is qualified to sign. Together we put it into the application’s specifications, its agents and their tools, and its review gates. The result is a repository the firm owns and runs with Docker Compose or Kubernetes on its own infrastructure.
Go deeper
The parts of Wildo this page draws on, each explained on its own page.
- AI assistants & task agents Application agents with their own instructions, tools and structured or conversational outputs.
- AI, retrieval & agent protocols Build assistants that retrieve knowledge, call application tools and interact through agent protocols.
- Identity, organizations & access Manage users, customer organizations, roles and service identities across application operations.
- Audit trails & data privacy Record accountable actions and handle personal-data requests, retention and erasure through application services.
- Providers, OAuth & external data Call provider operations, connect customer accounts and read or synchronize external business data.
- Docker & Kubernetes deployment Generate deployment configuration for your application services and their backing infrastructure.
Your expertise is the product.
The application is how that expertise reaches your clients, reviewed by your people and recorded for anyone who needs to check.
Start with a conversation.
Wildo is not self-service yet. Tell us what you want to create, and we will say plainly whether it fits and what happens next.