AGICOMPLY helps AI vendor founders and security leads answer an enterprise buyer's evidence request for one AI system. We review the records you supply against the requirements in scope, identify unsupported claims and evidence gaps, and prepare a traceable package the reviewer can examine.
Not sure you need the full package? Explore the optional $750 Reviewer Evidence Check
9f86d081…Have a specific buyer request? You can go straight to the complete Baseline. The $750 check is optional.
$750 fixed scope
For a team that wants to understand the evidence gaps before committing to the complete package.
$3,500 fixed scope
For one AI system facing a defined procurement, authorization or independent review that needs the complete evidence record.
One AI system and one agreed review context. Baseline timing is confirmed in written scope. No annual license is required. A request does not accept an engagement or authorize evidence intake.
SOC 2 readiness for AI SaaS is one possible review context. The applicable requirements and evidence window are confirmed during intake.
Bring one AI system and an actual buyer request. We agree the evidence work in writing so your team knows what to supply, approve and resolve.
Within the agreed scope, we organize the approved evidence, identify unsupported answers, prioritize gaps and prepare a traceable reviewer handoff. The $750 Check provides a focused gap report; the $3,500 Baseline provides the complete evidence package.
Name an accountable owner, confirm the system facts and supply authorized records. Your team must approve factual answers and evidence sharing, resolve missing information and implement remediation. Plan time for intake, factual checks and approvals.
The written scope defines the reviewer question set, timing, correction allowance and handling route. Any follow-up or later evidence changes must fit that agreement or be separately scoped. The reviewer makes the independent determination.
For an accepted U.S. workspace, direct PDF files can come from an approved folder or configured, authorized sources. Your team sets up and operates the runner and credentials. This is not a hosted one-click connection; source restrictions and human review still apply. Inspect the source setup and limits.
Keep public forms free of evidence, credentials and sensitive data. Wait for written scope and approved intake instructions before sharing records. Request written Baseline scope.
Inspect actual application database tests with synthetic records, separately observed effects and a portable evidence package. Compare a working control, a deliberately weakened test version, a false reported denial and the restored result.
Inspect recorded release evidenceExplore an interactive fictional review. Change shared evidence, trace the exact citations, and download a hypothetical review plan. The protected workspace uses the same calculation with your loaded question set.
Try the interactive change rehearsalPreparing for a bank risk or procurement review? Inspect a reproducible reference for agent permissions, approval, revocation and observed effects, with its limits stated alongside the results.
Explore Agent Action AssuranceThe trigger is a buyer, procurement team, authorizing party, or independent reviewer asking what evidence supports a requirement for a specific AI system.
Define the AI system, review context, applicable requirements, and supplied evidence population.
Connect the artifacts to requirements, preserve their source and review history, and make missing or weak support visible.
Deliver an evidence inventory, mapping summary, gap register, remediation sequence, and chain-of-custody statement for examination.
The applicable framework is established during scoping. AGICOMPLY prepares the evidence position; the customer, assessor, or authorizing party makes the decision.
An existing platform or adviser can continue managing controls and collecting evidence. For a specific AI review, AGICOMPLY works from the approved scope and supplied artifacts to prepare the reviewer-facing package.
Partner workflows and technical integration are scoped around a real customer review. We do not imply a prebuilt integration or transfer the partner's client relationship.
Explore the partner workstreamNIST AI RMF · NIST SP 800-53 · FedRAMP baseline language · OMB 2025 AI governance and acquisition memoranda · EU AI Act documentation context. References describe review language, not certification or endorsement.
AGICOMPLY was formed in Pennsylvania in February 2024. Founder Mark Gomez leads product direction, assurance methodology, customer discovery, and commercial delivery. The company is operational and offers paid, fixed-scope evidence reviews, with a public, bounded method that buyers can inspect before engagement. Customer history, certifications, approvals, and endorsements are never implied or borrowed.
Before you buy, inspect the completed sample, verification surfaces, public assurance claims, data boundary, and the person accountable for the work.
The Baseline remains fixed in scope. Your starting point depends on the responsibility you carry into the review.
See what the current record can support before an ATO, acquisition, or customer review begins.
Review this role pathOrganize the policies, records, owners, technical artifacts, framework version, and open conditions tied to a specific AI system and use case.
Review this role pathConnect supplied technical and governance records to the requirements in the assigned framework version, then isolate what is missing, stale, or unclear.
Review this role pathSupport an existing legal, advisory, assessment, or assurance engagement with a defined AI Evidence Appendix.
Review this role pathFollow one evidence relationship from intake through human acceptance, package issuance, and renewed examination after a material change.
A supplied record enters the bounded review scope.
The issued package preserves what was accepted at that point in time. A later artifact change does not rewrite history; it records that equivalent current reliance requires renewed reviewer examination.
Selecting a context changes the evidence questions and common dependencies. It does not establish legal applicability, certification, or control effectiveness.
Organize the supplied record around acquisition questions, system ownership, security evidence, human oversight, and current package limitations.
Move between the two states to see what changes when the supplied record becomes a bounded, reviewer-readable package.
Reviewers must reconstruct scope, ownership, evidence identity, and support relationships from disconnected materials.
Distributed across folders, email, and questionnaires.
Evidence may describe multiple versions or environments.
No attributable reviewer acceptance or limitations.
Source authority and current responsibility are uncertain.
Missing, stale, or contradictory support is not isolated.
No point-in-time manifest or reproducible review record.
The illustrative console assembles a bounded evidence position. It does not certify compliance, issue an ATO, or establish operating effectiveness.
One AI system, use case, owner, deployment context, and review boundary are identified.
system.boundary.recordedcurrentAn issued package records what was accepted at that point in time. A changed artifact triggers renewed examination rather than silently carrying the prior conclusion forward.
A framework name alone is not enough. Reviewers need to know which version was used, what source was reviewed, what requirements were in scope, and which evidence relationships were accepted.
Record the assessment date, scope basis, and exact framework version relied upon without overwriting prior assignments.
Examine this assurance propertyAssociate authoritative source location, content identity, and attributed review with the framework version used in the package.
Examine this assurance propertyPublication gates require source attribution, review decisions, control relationships, evidence guidance, and applicability coverage.
Examine this assurance propertyUpdated interpretations require a new version, preserving the content and scope relied upon by prior point-in-time reviews.
Examine this assurance propertyAGICOMPLY organizes supplied evidence into a point-in-time AI assurance package tied to the framework version and assessment date used for review. The engagement identifies what is present, how it supports the requirements in scope, what remains unclear, and what to address next.
Explore the engagementA structured register of supplied artifacts, their source, format, date, owner, and content hash.
Human-verified links between supplied evidence and the review requirements within the agreed scope.
A bounded record of missing, unclear, stale, or insufficiently supported evidence items.
Sequenced evidence actions organized around review dependencies and submission priorities.
A record of evidence handling, SHA-256 content hashing, and review activity during the engagement.
Hybrid evidence candidate mapping accelerates organization; human verification determines which relationships belong in the review package and records the limitations of that decision.
Review methodologyVanta, Drata, Credo AI, Monitaur, Holistic AI, and RegScale operate in important upstream layers. AGICOMPLY provides the fixed-scope reviewer handoff that can sit after them.
Recurring compliance operations, evidence collection, continuous monitoring, and audit workflow.
Compare the assurance stackEnterprise AI inventory, governance, policy, risk, regulatory context, monitoring, and lifecycle records.
Compare the assurance stackContinuous controls monitoring, cyber GRC, compliance-as-code, and broader ATO or RMF workflow.
Compare the assurance stackOne bounded evidence package stating what supplied artifacts support, what remains unresolved, and what must be fixed first.
Compare the assurance stackEach path uses the same $3,500 fixed-scope Baseline. The review context changes; the evidence method does not.
Control and operating-period evidence organized before an independent CPA examination or enterprise customer review.
Review this pathA bounded, reviewer-facing evidence package for AI vendors answering European procurement, customer-assurance, and EU AI Act documentation requests.
Review this pathDisclosure, marking, detector testing, publication, and approval evidence organized for reviewer examination.
Review this pathEvidence packages aligned to the review language used in acquisition, ATO, NIST AI RMF, and NIST SP 800-53 contexts.
Review this pathPoint-in-time evidence packages for operational AI used in regulated and high-consequence environments.
Review this pathA bounded, white-label AI Evidence Appendix for advisers, assessors, law firms, and assurance teams.
Review this pathThese pages explain how AGICOMPLY approaches AI ATO readiness, procurement evidence, chain of custody, version-aware scope, and human-verified control mapping.
Prepare system-boundary, control-design, operating-period, and AI-specific evidence before a CPA examination or enterprise security review.
Examine the evidence approachEstablish what supplied evidence supports an ATO or procurement review before the reviewer has to reconstruct it.
Examine the evidence approachOrganize system records, framework-version scope, control mappings, gaps, remediation priorities, and chain-of-custody properties into one bounded package.
Examine the evidence approachPrepare system identity, role and scope records, buyer-requested documentation, Article 50 evidence where applicable, data-handling conditions, gaps, and accountable decisions for European review.
Examine the evidence approachDocument how supplied evidence was identified, hashed, mapped, reviewed, and included in the point-in-time package.
Examine the evidence approachPreserve which framework version, source, requirement, reviewer decision, and assessment date each included conclusion depended on.
Examine the evidence approachUse deterministic candidate mapping for organization while preserving attributable reviewer acceptance and limitations.
Examine the evidence approachThe Procurement Vault consolidates commercial scope, assurance materials, security and privacy statements, the Evidence Standard, the Evaluation Packet, and the Internal Approval Brief.
The Public Assurance Register exposes implementation status, verification method, evidence reference, review date, and limitation for every material public claim. The Package Verifier demonstrates independent manifest integrity comparison without exposing customer records.