Human review before delivery
AI-agent output is treated as preparation work. A responsible human reviewer checks the package before client use.
Trust & governance
The operating model is designed for practical outsourcing: fast preparation, accountable review, and clear boundaries around external use.
Trust controls
AI-agent output is treated as preparation work. A responsible human reviewer checks the package before client use.
Deliverables are organized around source files, assumptions, open items, and reviewer notes so decisions remain traceable.
IKANISA prepares operations work and decision-support packages. It does not issue licensed audit, legal, tax, or assurance opinions.
Exceptions, missing inputs, and review questions are escalated early so the delivery pod does not hide uncertainty.
Control map
Operating control
Every delivery package moves through source, preparation, quality control, and human review before it can leave the workfile.
Files, assumptions, owners, and missing inputs are listed before drafting.
Agents prepare workfiles inside the agreed scope and evidence boundary.
Exceptions, inconsistencies, and unsupported claims are surfaced.
A responsible reviewer approves the package before external use.
Operating standards
Diligence library
Leadership proof must be approved before publication.
AI-assisted delivery with human accountability.
High-level controls without unverified compliance claims.
Clear service boundaries for institutional buyers.
Partner claims require approval before publication.
Global remote delivery, with no invented offices.
Practical safeguards, with legal-review gaps called out.
Accessible public information is part of the diligence surface.
Basic cookie choices for the public website.
Boundary
Generated packages remain preparation material until a human authorizes the next step. External filing, submission, sharing, and regulated opinions stay outside the automated delivery path.
Book strategy review