Syntic
Deployment safety

AI Employees that act.
Controls that hold.

An AI Employee that takes a call, runs a credit pull, sends a payment or ships to production is not a chatbot. Safety is built in at design, enforced at runtime and kept honest by human oversight. Not a feature you enable — how the platform works.

Talk to safety →Request the safety pack
  • Human oversightBuild review and escalation into consequential AI workflows.
  • Bounded authorityDefine what an AI Employee may access and do.
  • Operational visibilityMake activity, exceptions and outcomes easier to review.
  • Continuous improvementStrengthen safety as deployments and requirements evolve.
Four layers

When an AI Employee acts,
the consequences are real.

A bad answer in a collections call is an FDCPA violation. A bad action in a payment workflow may be unrecoverable. Every Employee — hired from the Directory or custom-built — inherits the same four layers. None are optional add-ons.

Layer 01

Design-time safety

Define authority, permissions and intended use before deployment.

  • Scoped accessApply least-privilege principles to credentials, data and integrations. Confirm supported restrictions for each product.
  • Authority boundariesIdentify decisions and actions that should require explicit authorization or review.
  • Content policiesSet appropriate instructions, prohibitions and review criteria for the intended workflow.
  • Data boundariesAssess how knowledge sources, workspace permissions and sensitive information are separated.
  • Voice and consentReview applicable consent, recording, disclosure and voice-use requirements before launch.
  • Regulatory scopingAssess the relevant legal framework with qualified counsel and confirm supported safeguards.
Layer 02

Runtime safety

Supervise AI behavior during operation and respond to exceptions.

  • Approval workflowsIdentify consequential actions that should pause for human authorization. Available approval mechanisms vary by product.
  • Activity monitoringEvaluate supported visibility into conversations, executions and external actions.
  • Output safeguardsCombine model-level safeguards, product policies and human review according to risk.
  • Rate limits and outreachApply appropriate volume, timing, consent and opt-out controls for communications.
  • Quality evaluationUse sampling, testing and escalation to detect errors or changes in behavior.
  • Integration boundariesRestrict connected services and credentials to necessary permissions.
Layer 03

Human oversight

Keep people responsible for high-impact outcomes.

  • Human escalationDesign routes for customers and operators to reach a person when needed.
  • InterventionEvaluate pause, handoff or takeover options supported by the deployment.
  • Clear accountabilityAssign owners and reviewers to sensitive workflows and exceptions.
  • Review decisionsRequire human judgment where legal, financial, clinical or safety stakes are high.
  • Multi-perspective reviewFor complex decisions, consider independent analysis and human validation rather than a single unchecked AI judgment.
  • AI transparencyPlan clear disclosures wherever required or appropriate.
Layer 04

Audit and accountability

Preserve appropriate evidence and learn from outcomes.

  • Execution recordsIdentify which inputs, outputs and action metadata must be retained for oversight.
  • Approval historyRecord important authorizations and reviewer decisions where supported.
  • Change managementTrack significant changes to instructions, permissions and deployment configurations.
  • Voice recordsReview lawful recording, disclosure, access and retention requirements.
  • Incident evidencePreserve information needed to investigate unexpected behavior.
  • Export and retentionConfirm available log formats, retention periods and integrations before making contractual commitments.
  • Integrity assuranceAdditional audit integrity measures are part of our security direction; no universal cryptographic log guarantee is claimed.
By deployment stage

You set the posture.
The platform enforces it.

A pilot needs a different posture than a national operation. The platform never pushes you toward less oversight than you're comfortable with — you decide what to activate, and when to relax it.

  1. 01

    Pilot · first 1–3 Employees

    Maximum oversight. Approvals on every consequential action, live monitoring on every conversation, daily execution review, conservative authority limits.

  2. 02

    Production · operational workforce

    Calibrated posture. Thresholds tuned to your risk tolerance, sampled QA, automated evaluations with human review of exceptions.

  3. 03

    Scale · running core operations

    Optimised posture. Approvals for true exceptions, weekly trend reviews, Council deliberation on the highest-stakes decisions.

Regulated industries

Compliance built in.
Not bolted on.

Phrasing, disclosures, escalation rules and approval gates are part of the Employee design from the start.

Collections

FDCPA

Review debt-collection language, consumer rights, disputes and escalation requirements before deployment.

Healthcare

HIPAAClinical oversight

Assess PHI handling, contracting requirements and clinician review; do not assume a BAA or medical-device clearance.

Financial services

Model riskConsumer protection

Evaluate governance, explainability, authorization and sector-specific supervisory obligations.

Public sector

ProcurementSecurity review

Government workloads require separate eligibility, authorization and deployment assessments.

Insurance

State requirementsHuman review

Review claims processes, licensing and customer-impacting decisions.

Education

FERPAChild privacy

Consider student privacy, age-related restrictions, accessibility and institutional oversight.

Incidents & enterprise

When things go wrong.
And when stakes are higher.

We don't wait for a customer to notice something is wrong. For high-risk deployments, additional controls sit on top.

Incident response

  • Detection and reportingEstablish channels to identify and report unexpected AI behavior.
  • InvestigationAssess impact, preserve evidence and coordinate technical and customer response.
  • NotificationCommunicate incidents according to applicable law and contractual obligations.
  • Lessons learnedUse findings to improve evaluations, safeguards and operating procedures.
  • Emergency interventionPlan a reliable pause or shutdown procedure and confirm the controls available for each deployment.

Custom & Enterprise

  • Deployment scopingReview higher-risk workflows before committing to production use.
  • Governance designDiscuss approval roles, permissions and operational oversight.
  • Regional requirementsAssess residency, sovereignty and regulatory requirements case by case.
  • Independent reviewDiscuss documentation and evidence that may be available for qualified external assessments.
  • Commercial protectionsAny insurance, indemnification or special liability terms require a signed agreement.
How it's built

The practice
behind the controls.

Researchers can reach us at support@syntic.ai. Vulnerabilities and safety concerns go through responsible disclosure — our team can review reports and follow up as appropriate.

  • Pre-deployment evaluationTest intended use cases and failure modes before increasing autonomy.
  • Adversarial testingUse red-team thinking to identify misuse, prompt injection and unsafe actions.
  • Feedback and iterationLearn from reported concerns, customer experience and operational evidence.
  • Research directionContinue developing responsible AI practices as the platform and industry mature.
The limits

Real, enforced controls.
Not magic.

Honest accounting of limits is itself a safety property. Any vendor that promises zero incidents is lying to you about something important.

No zero-risk promise

AI systems can make mistakes. Safeguards reduce risk but cannot eliminate it.

Human judgment matters

Organizations remain responsible for defining appropriate authority and reviewing consequential outcomes.

Not a certification

Safety design does not constitute SOC 2, ISO 27001, FedRAMP or sector-specific regulatory approval.

Capabilities vary

Specific controls, integrations and response commitments must be verified for each product and contract.

Get in touch

Reach the team that
owns deployment safety.

Safety questionssecurity@syntic.aiPlatform controls, safety scoping and regulated-industry engagements.
Concerns & incidentssecurity@syntic.aiContact the security team for reporting and next steps.
Research collaborationsupport@syntic.aiAcademic researchers, AI safety organisations and red teams.
Responsible disclosuresyntic.ai/legal/security-disclosureInitial response within 3 business days; advisories published for significant resolved findings.
Deployment safety

Build the future of AI with responsibility at its core.

Talk to the team, or request our deployment safety pack.

Talk to safety →Report a safety concern