Solutions
Built for workflows where control is part of the outcome.
Deeplinq gives regulated operators a common enforcement and evidence layer without prescribing their policy or replacing accountable decision-makers.
Shared control model
Every workflow answers the same four questions.
Identity, permitted evidence, decision authority, and proof compose into a reusable boundary across industries.
Operating risk bounded
Identity
Who is asking
Evidence
What may be used
Authority
Who must decide
Unbounded action
No approval path
Shared requirement
Different sectors. The same control questions.
The language changes by industry, but the production boundary remains consistent.
- 01
Who is asking?
Authenticate the caller, bind the organization, and resolve live role, team, model, dataset, and tool authority.
- 02
What may leave?
Apply content screening, deployment boundaries, and approved provider routes before sensitive data reaches an external system.
- 03
Who decides?
Keep consequential tool actions behind a human approval gate and make every terminal outcome explicit.
- 04
What can be proven?
Correlate controls, model activity, costs, and external calls in a verifiable record that excludes prompts and answers.
Industry patterns
Start from the operating risk.
These pages describe reference workflows, not customer claims. Each one maps to controls the engine currently enforces.
Banking
Control model, data, and agent access across regulated banking products and operations.
02AML
Ground investigations in approved evidence and preserve human authority over disposition.
03Telecom
Unify high-volume support and operations across markets, providers, and customer boundaries.
04Education
Ground student and staff assistance in approved knowledge, scoped access, and cited evidence.
05Legal services
Keep legal research and matter workflows inside explicit client, data, and approval boundaries.
06Accounting
Review policies, spreadsheets, and evidence with attributable usage and human-controlled actions.
07Public sector
Make identity, purpose, evidence, and oversight visible in public-service AI workflows.
Next step
Bring one controlled workflow.
We will map its users, evidence sources, model options, approval points, cost boundary, and audit requirements.