Safety-first / migration-ready / performance-leading

Wave 1 products

• PART III

  AIVAON Safeguard

  Continuous AI safety and red-teaming — adversarial testing, prompt-injection detection, exfiltration monitoring, bias evaluation, compliance-specific safety validation — as integrated capability that extends the Trust substrate into active proof.

  Product detail →

  Differentiated depth

  Continuous adversarial scenario library executed against deployed agents on a continuous basis, producing per-scenario pass/fail evidence and aggregate safety posture metrics with bias evaluation across demographic dimensions and jurisdiction-specific compliance suites maintained by the platform's compliance-engineering function in coordination with regulatory liaison.

  Competitive replicability

  0.15 / 1.00

  lower = harder to replicate

  Addressable horizon

  12 months

  Engineering owner

  ai-safety-engineering-program

  Visionary-validation evidence (4)

  • analyst_forecast: AI safety platform spend projected 5x growth 2026-2028
  • competitor_investment_signal: every major LLM platform launching dedicated safety surface
  • regulator_signal: EU AI Act enforcement requires continuous safety evidence
  • pilot_outcome: regulated-industry pilot achieved 73% reduction in deployment authorization friction

  Catalog integration dependencies

  agents, trust, observability, intelligence, studio

• PART VIII

  AIVAON Migrate

  Competitive displacement as a structural product — automated configuration translation from Vapi / Retell / Bland / Twilio Flex / Google Contact Center AI / Genesys, parallel-operation traffic splitting, data migration tooling, and migration-success validation.

  Product detail →

  Differentiated depth

  Translator libraries with high-fidelity per-platform mapping logic (Vapi, Retell, Bland, Twilio Flex, Google Contact Center AI, Genesys Cloud), parallel-operation traffic-splitting infrastructure with comparative observability, data migration tooling preserving residency through cutover, and the migration-success validation methodology that produces empirical cutover-confidence signals.

  Competitive replicability

  0.20 / 1.00

  lower = harder to replicate

  Addressable horizon

  18 months

  Engineering owner

  competitive-engineering-program

  Visionary-validation evidence (3)

  • competitor_investment_signal: incumbent platforms not investing in displacement-friendliness
  • customer_advisory_sentiment: top displacement blocker is migration-risk perception
  • pilot_outcome: 8 of 10 migration pilots completed cutover within 90 days

  Catalog integration dependencies

  studio, observability, trust, intelligence

• PART IX

  AIVAON Benchmark

  Public, reproducible, methodology-transparent benchmarking across latency / quality / connectivity / cost / compliance / sovereignty / scale, plus the interactive TCO calculator that converts benchmark publication into commercial engagement.

  Product detail →

  Differentiated depth

  Methodology transparency permitting independent replication, raw-data accessibility, interactive TCO calculator computing the platform-comparison TCO for prospect-specific deployment characteristics, multi-channel benchmark distribution (website with structured-data markup / analyst relations / public relations / sales enablement / partner enablement), and quarterly benchmark refresh cadence with interim updates on competitive change.

  Competitive replicability

  0.25 / 1.00

  lower = harder to replicate

  Addressable horizon

  12 months

  Engineering owner

  category-creation-program

  Visionary-validation evidence (3)

  • analyst_forecast: structured-data-driven AI procurement evaluation rising to 40% of evaluation cycles by 2027
  • competitor_investment_signal: no competitor publishes methodology-transparent benchmarks
  • pilot_outcome: prospects with TCO calculator engagement convert at 2.4x baseline rate

  Catalog integration dependencies

  intelligence, trust, observability, marketplace