A complete platform a company runs inside its own environment to build, run and control AI agents end to end. Agents work inside real limits, a named person approves what goes beyond them, and every action is kept in a record an auditor can check.
Highline ConsoleLive exampleIt does not only answer questions. It credits a guest, approves a loan, changes a record or sends a payment. That is where the value is, and where the risk is.
In a company that is regulated or holds sensitive data, the data cannot leave. Nothing counts what agents have already done, so many small allowed actions can add up to one breach.
Highline AI runs the agent inside your environment. It counts what AI has done to each customer, account or record across every agent and system. A named person approves anything above the limit.
Each team sees what its agents did, what waits for a named person and what was refused. Below, payments at a building society.
A hotel sets a limit on goodwill per guest stay. Three agents in three systems each credit the same guest. Move any slider and watch the total.
Needs approval. The action waits for a named person at the hotel. No answer means no. The limit is in the business's own units, pounds, records or permissions, never a count of actions, because an agent can split one action into many.
An agent that only answers questions needs none of them. An agent that opens accounts, moves money or changes records needs every one.
Runs in your cloud, your data centre or fully offline. Any model. No data leaves.
The agent acts inside your booking, banking or document systems, not a chat window.
A cap on the total across every agent and system. Patent pending.
A named person approves anything above the limit. No answer means no.
Every action, who approved it and why, sealed and timestamped.
Hover a card to see what it protects against.
In a company that is regulated or holds sensitive data, agents cannot be deployed without this end to end control, governance and traceability.
The agent proposes an action. A separate part decides whether it is allowed. A third part carries it out with credentials the agent never sees. If any check fails, the action does not happen and the attempt is recorded.
Runs the agent in a sealed sandbox with no credentials. It can only ask.
Compares the live server to its signed, approved setup. If anything changed, the action stops.
Reads the running total and applies the rules your compliance team wrote.
Asks the named person when the limit requires it. No answer means no.
The only parts that hold credentials. They act and update the total.
Writes every step to a chained, timestamped record you can verify without Highline AI.
Four layers. Each card names the risk it removes.
The agent proposes, a separate part decides, a third part acts. They exchange signed tokens and nothing else.
Highline AI keeps a signed copy of each server's approved setup and compares the live server to it.
Every AI change to a customer, account or record is counted across all agents and systems. Patent pending.
Every action, decision and approval is sealed with a timestamp from an independent authority.
They build and run good agents. The difference is where the data, the governance and the record live.
Any company that has to answer for what its AI does, to a regulator, a board, shareholders or customers. Regulated or not. Sold direct and through partners.
AI must stay inside the bank's thresholds, with proof. Weak controls cost UK banks tens of millions in fines.
Guest facing AI hands out credits, points and vouchers across several systems, so the cap must be per guest.
AI that drafts or changes trial documents needs a named reviewer on every change and a record the regulator can inspect.
AI that processes patient data needs a named reviewer and a record. Patient data stays inside.
AI that checks applicants and matches buyers to sellers works on personal data, financial data and client money.
AI that drafts budgets and tracks campaign spend works on client money and client data.
Hover a sector to see an example limit.
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