Sold by: Kriv AI
Kriv AI deploys a production drift-detection and continuous-evaluation pipeline on Amazon Bedrock. Monitors 7 drift vectors, data drift (PSI / KS / Wasserstein / Jensen-Shannon), concept drift (Claude-as-judge), prompt drift (version-control diff), RAG retrieval drift (recall@k / NDCG / MRR + embedding shift), tool-use drift (MCP call frequency / success rate / latency), cost drift (token creep + AWS Budgets), champion-challenger (Bedrock Opus 4.6 vs Sonnet 4.6 vs Haiku 4.5 via SageMaker Experiments). Integrates Amazon SageMaker Model Monitor + Bedrock Model Invocation Logging + Amazon CloudWatch + QuickSight + AWS Step Functions + Claude on Bedrock as LLM-judge. Regulated-industry evidence aligned to SR 11-7 ongoing monitoring + NAIC Model Bulletin + EU AI Act Article 15 + Article 72 + FDA SaMD PCCP + SOC 2 CC7 + HIPAA §164.308(a)(1)(ii)(D). Three tiers: $45K / $75K / $110K + $15K Extra Model. MDF-eligible. AWS Select + Anthropic CPN.
Overview
Production AI without continuous monitoring is regulatory exposure. Bedrock models degrade silently: data drift, concept drift, prompt drift, RAG retrieval drift, tool-use drift, and cost drift all fail without alerts, and until now, no Bedrock-native, drift-specific, fixed-fee consulting SKU existed on AWS Marketplace.
Existing AWS Marketplace listings are either general MLOps foundations (Slalom, Caylent, Rackspace, Mission Cloud, Quantiphi, Tiger Analytics at $50K–$200K custom-priced), SaaS monitoring tools Customer operates (Arize AI $50K–$250K/yr, Fiddler AI $60K–$300K/yr, WhyLabs $25K–$100K/yr, Evidently AI $15K–$75K/yr, Datadog, New Relic, Dynatrace), or open-ended Big-Four SI SOWs ($200K–$500K). None offer fixed-fee, Bedrock-native, drift-specific implementation with regulator-defensible evidence packages. Category is MDF-eligible under AWS Agentic AI Competency.
Regulators have moved faster than monitoring tooling. SR 11-7 / OCC 2011-12 require ongoing monitoring as essential MRM. NAIC Model Bulletin on AI (Dec 2023, 20+ state adoptions) requires insurers to validate AI on ongoing basis. EU AI Act Article 15 requires high-risk AI to maintain accuracy, robustness, cybersecurity; Article 72 mandates post-market monitoring with evidence for AI Office / NCA review. FDA SaMD PCCP (Dec 2024) requires change-control monitoring. SOC 2 Type II CC7 requires documented monitoring. OWASP Top 10 for LLM names overreliance (LLM09), continuous evaluation is the mitigation.
Seven drift vectors instrumented.
Data drift: PSI, Kolmogorov–Smirnov, Wasserstein, Jensen–Shannon on prompt distributions, RAG inputs, tool-call parameters.
Concept drift: Claude-as-judge output-quality regression tracking against frozen golden dataset; precision / recall / F1 deltas flagged.
Prompt drift: upstream prompt template diff tracking with version control + CI/CD.
RAG retrieval drift: KB freshness; recall@k / NDCG / MRR; embedding-space shift via periodic re-vectorization.
Tool-use drift: MCP / tool-call frequency, success rate, latency regression, argument distribution shift.
Cost drift: token-usage creep; per-agent / per-tenant cost trend; AWS Budgets thresholds.
Champion-challenger: automated A/B (Claude Opus 4.6 vs Sonnet 4.6 vs Haiku 4.5) via SageMaker Experiments.
Automated alerting. CloudWatch Alarms → EventBridge → SNS to Jira / ServiceNow / PagerDuty / Opsgenie / Slack / Microsoft Teams.
Reference architecture. SageMaker Model Monitor + Bedrock Model Invocation Logging → S3 monitoring data lake with Object Lock → Glue + Athena drift analytics → CloudWatch Metrics + Alarms → QuickSight dashboards → Step Functions orchestration → Claude on Bedrock as LLM-judge → SageMaker Experiments for champion-challenger → EventBridge for incident routing.
Week-by-week.
Week 1 Scoping + baseline capture (model inventory; threshold design; alert-channel plan).
Week 2 SageMaker Model Monitor + Bedrock Model Invocation Logging deployment + S3 + Glue + Athena.
Week 3 Core drift detectors (data + concept + prompt) + CloudWatch Alarms + EventBridge: Foundation closes (30-day warranty).
Week 4 Standard: advanced drift (RAG + tool-use + cost) + QuickSight dashboards + CI/CD alert integration (45-day warranty).
Week 5 Enterprise: champion-challenger via SageMaker Experiments (Opus 4.6 / Sonnet 4.6 / Haiku 4.5); regulated-industry evidence (SR 11-7, NAIC, EU AI Act Article 72).
W6 Enterprise: sibling integration (N29 + N31 + N24); 60-day hypercare.
Three tiers. Foundation $45K (4 wk; 1 model; data + concept + prompt drift; CloudWatch Alarms; 30-day warranty) for AI-native Series B–E + Fortune 1000 first internal pilot. Standard $75K (5 wk; up to 5 models; advanced drift + QuickSight + CI/CD multi-channel alerting; 45-day warranty) for mid-sized multi-model + SOC 2 Type II renewal + fintech / healthtech production MLOps. Enterprise $110K (6 wk; up to 10 models; regulated-industry drift evidence: SR 11-7 + NAIC + EU AI Act Article 72 + FDA SaMD PCCP; champion-challenger across Opus 4.6 / Sonnet 4.6 / Haiku 4.5; 60-day hypercare) for regulated, G-SIB banks, top-25 payers + pharmas. Optional Extra Model $15K each.
Important disclosures. Kriv does NOT operate pipeline post-deployment (unless Managed Service retainer). Does NOT retrain Customer models, detection only; remediation (retraining, threshold adjustment, prompt updates) is Customer's. Issues no SOC 2 / HIPAA / HITRUST / ISO certifications. No legal / regulatory / compliance advice. No 100% drift detection guarantee, statistical tests are probabilistic. No SageMaker Model Monitor / Bedrock API stability guarantee. AWS + Anthropic + Bedrock + LLM-judge consumption separate. No regulator-outcome guarantee. Anthropic CPN membership does not constitute endorsement.
Highlights
- First fixed-fee Bedrock-native drift + continuous-eval consulting SKU on AWS Marketplace, 7 drift vectors instrumented.** Data drift (PSI / Kolmogorov-Smirnov / Wasserstein / Jensen-Shannon); concept drift (Claude-as-judge output-quality regression); prompt drift (version-control diff); RAG retrieval drift (recall@k / NDCG / MRR + embedding shift); tool-use drift (MCP call frequency / success rate / latency); cost drift (token creep); champion-challenger (Opus 4.6 vs Sonnet 4.6 vs Haiku 4.5)
- Amazon SageMaker Model Monitor + Bedrock Model Invocation Logging + Amazon CloudWatch + QuickSight + AWS Step Functions + Claude on Bedrock as LLM-judge + SageMaker Experiments for champion-challenger.** S3 Object Lock monitoring data lake for regulated-industry audit. Glue + Athena drift analytics. CloudWatch Alarms → EventBridge → SNS to Customer Jira / ServiceNow / PagerDuty / Opsgenie / Slack / Microsoft Teams. CI/CD alert integration via GitHub Actions / CodePipeline / GitLab CI
- Regulated-industry evidence: SR 11-7 ongoing monitoring (OCC / FRB / FDIC MRA / MRIA); NAIC Model Bulletin ongoing validation; EU AI Act Article 15 + Article 72 post-market monitoring; FDA SaMD PCCP change-control; SOC 2 CC7 System Operations; HIPAA §164.308(a)(1)(ii)(D) ongoing evaluation.** Three tiers: $45K Foundation (1 model, 3 drift vectors); $75K Standard (5 models, 6 vectors); $110K Enterprise (10 models, 7 vectors + champion-challenger + regulated evidence). MDF-eligible.
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Primary contact. info@kriv.ai · +1-732-433-5564 · https://kriv.ai/support
Response SLA. First response within 2 US business days (Mon–Fri 9 am – 6 pm ET, ex-US federal holidays). Active engagements: Engagement Lead within 4 business hours weekdays. Post-incident (silent model degradation, unexpected output, cost overrun) or post-MRA/MRIA engagements compress to same business day.
Onboarding SLA. First customer contact within 2 US business days of buyer inquiry / private-offer acceptance. Kickoff within 1–2 weeks of SOW; 3–5 business days post-incident.
Escalation. (1) Engagement Lead (named in SOW) → (2) Practice Director (info@kriv.ai ) → (3) CEO Abhinav Dangri (info@kriv.ai ).
Communication. Dedicated Microsoft Teams channel; weekly 60-min video checkpoint; Friday written status. Customer SMEs 3–5 hrs/week (Head of AI Platform, VP Engineering, CISO, Head of MLOps, CAIO, Head of MRM for regulated Customers).
Handoff. Word/Excel/PDF in customer secure share; drift detectors + thresholds as Git repo (Python / JSON); CloudWatch + QuickSight dashboards as CloudFormation templates; Step Functions state machines as JSON; regulated-industry evidence (Enterprise) as Excel indexed to control IDs.
Out of scope. Does NOT operate pipeline post-deployment (unless Managed Service retainer). Does NOT retrain Customer models, detection only. Issues no certifications. No legal / regulatory / compliance advice. No 100% drift-detection guarantee. No SageMaker Model Monitor / Bedrock API stability guarantee. No regulator-outcome guarantee.
AWS + Anthropic-side billing. AWS infrastructure + Anthropic API + Bedrock Claude consumption (incl. LLM-judge) separate.
Holiday coverage. Closed on US federal holidays.