Overview
Why AI Fails After Launch
Most AI projects fail not at launch but after it. Models drift as data changes, costs creep, providers ship new versions, demand spikes, and systems that quietly degrade stop moving the business metrics they were built for. AIDayTwo by Strongly is the managed service built around that problem.
AIDayTwo pairs a platform that monitors continuously with data scientists and engineers who stay engaged on the work only people can do. The platform watches quality, uptime, drift, cost, and usage. The team watches those signals alongside the business outcome each solution was built to move - and acts when either drifts, with new models, retraining, tuning, new features, or a fast path to human intervention.
Industry Example: Retail Demand Forecasting
For retail and e-commerce teams where AI-driven demand forecasting drives sell-through and inventory efficiency, AIDayTwo detects data drift caused by seasonal shifts or promotional events and triggers automatic retraining validated through champion-challenger comparison before degraded predictions impact revenue. The platform accounts for event-driven and seasonal spikes so models stay accurate when demand surges during peak periods like Black Friday or back-to-school.
Two Ways In
- Continue - For solutions Strongly built. Day two follows with no gap, already instrumented and mapped into your context layer.
- Adopt - For solutions your team built. A short onboarding (typically 2-4 weeks) reviews the system, instruments it, baselines quality and cost, and maps it into the context layer before management begins.
Named Integrations
AIDayTwo deploys in your AWS environment - your VPC, your account - and integrates with Amazon Bedrock, Amazon SageMaker, and AWS CloudWatch for native observability. The AI-Gateway routes across multiple providers including OpenAI, Anthropic, and Azure OpenAI, enabling multi-provider failover so a single vendor outage does not become yours.
What a Managed Engagement Includes
- Monitoring and Observability - Full execution tracing, logs, and evaluations on every workflow and agent. Quality, latency, uptime, and output accuracy tracked continuously with model and user-level analytics from the AI-Gateway.
- Business Outcome Monitoring - Beyond system health, the business metric each solution was built to move - such as attach rate, reactivation rate, or sell-through - is tracked on your executive dashboard. If the commercial result drifts, the team acts.
- Model and Prompt Updates with Provider Resilience - As providers ship new models or deprecate old ones, Strongly re-routes, re-tunes, retrains, and updates prompts so performance holds or improves. Routing fails over across providers.
- Drift Detection and Retraining - Data drift and concept drift are detected automatically. Changes are validated with regression evaluations, champion-challenger comparison, and A/B testing before reaching production.
- Seasonality and Peak Readiness - Event-driven and seasonal shifts are accounted for in both models and infrastructure so solutions stay accurate and available when demand spikes.
- Security and Governance - Role-based access, audit logs, encryption in transit and at rest, vulnerability management, penetration testing, and attested versioned policies that allow, block, or hold agent actions before execution. Backed by independent third-party security attestations.
- Adversarial and Red-Team Testing - Ongoing probing for prompt injection, jailbreaks, and misuse to find AI-specific failure modes before they surface in production.
- Cost Management and FinOps - Infrastructure, solution, and model costs monitored around the clock with budgets at component and solution level, delivering up to 70% lower AI spend through intelligent routing and caching.
- Reporting - Regular performance reviews tied to agreed business metrics, each with recommendations for the next improvement, plus SLA-backed escalation paths.
Platform Capabilities
AI-Gateway for analytics and model routing, Model Registry with drift detection and automatic retraining, workflow and agent monitoring with trace-level detail, active governance enforcement, and FinOps tagging and budget controls.
Engagement Model
AIDayTwo is delivered as a continuous subscription with SLA-backed service levels. The Business Tier provides 99.5% monthly uptime with business-hours support. The Enterprise Tier delivers 99.9% monthly uptime with full 24/7 coverage.
Book a 30-minute AI Operations Assessment to scope your environment and define your engagement path. Visit strongly.ai or contact sales@strongly.ai to get started.
Highlights
- Platform + People: Continuous automated monitoring paired with engaged data scientists and engineers who re-route, retrain, tune, and add new capabilities as models and data change. Integrates with Amazon Bedrock, Amazon SageMaker, and AWS CloudWatch while routing across OpenAI, Anthropic, and Azure OpenAI for multi-provider resilience. Enterprise tier delivers 99.9% monthly uptime SLA with 24/7 support.
- Business Outcome Monitoring with Measurable Impact: Tracks the business metric each AI solution was built to move - such as attach rate, reactivation rate, or sell-through - not just system health. Acts when commercial results drift through retraining, re-routing, and tuning. Intelligent routing and caching delivers up to 70% lower AI spend. P1 incidents acknowledged within 1 hour with 4-hour resolution target.
- Security, Governance and Adversarial Testing: Attested versioned policies enforce actions before execution with tamper-evident decision logs. Multi-provider failover prevents single-vendor outages. Ongoing red-team testing probes for prompt injection, jailbreaks, and misuse. Backed by independent third-party security attestations, role-based access, encryption in transit and at rest, and periodic penetration testing.
Details
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Pricing
Custom pricing options
How can we make this page better?
Legal
Content disclaimer
Support
Vendor support
Support Tiers
AIDayTwo provides SLA-backed support across two tiers:
Business Tier: Support during business hours (Eastern Time, Monday through Friday, excluding federal holidays) with 24/7 coverage for critical P1 incidents. 99.5% monthly uptime commitment.
Enterprise Tier: Full 24/7 support across all incident priorities with a defined escalation path. 99.9% monthly uptime commitment.
Incident Response Targets
- P1 Critical: 1-hour acknowledgment, 4-hour resolution target
- P2 High: 4-hour acknowledgment, 24-hour resolution target
- P3 Low: 1 business day acknowledgment, 5 business day resolution target
Onboarding and Engagement Scoping
Continue Path: For solutions Strongly built via AI Assembly. Day two management begins immediately at launch with no gap - systems are already instrumented and mapped into your context layer.
Adopt Path: For solutions your team built. Onboarding begins with a short assessment (typically 2-4 weeks) that reviews your system architecture, instruments monitoring, baselines quality and cost metrics, and maps the solution into the context layer before active management begins. Milestones include: initial system review (week 1), instrumentation and baselining (weeks 2-3), and context-layer mapping with management handoff (week 3-4).
Ongoing Deliverables
Beyond incident response, the service includes continuous monitoring, monthly uptime reports, quarterly business reviews against agreed metrics, and a fast route to human intervention or rollback when model behavior drifts.
Getting Started
Book a 30-minute AI Operations Assessment to scope your environment. Contact sales@strongly.ai or visit strongly.ai.