Generative AI companies are no longer experimental vendors, they are becoming core technology partners for enterprises automating high-friction, knowledge-intensive workflows across industries. In enterprise contexts, generative AI development companies design and deploy domain-trained AI systems that automate workflows, augment decision-making, and…
Engineering-led application management, proactive performance monitoring, and continuous improvement, the ongoing partnership that keeps your production systems reliable, secure, and evolving.
A support contract is not the same as a managed services partnership. One fixes what breaks.
The other prevents it from breaking in the first place.
One fixes what breaks. The other prevents it from breaking.
Traditional Application Support:
- Reactive; responds when something breaks
- Ticket-based problems go into a queue and wait
- Junior engineers handling issues the original team built
- SLAs measured in response time, not resolution quality
- Handoff mentality; we built it, now you maintain it
CaliberFocus Managed Services:
- Proactive; monitors and acts before users notice problems
- Engineering-led the team that knows your system manages it
- Continuous improvement performance, security, and capability evolve
- SLAs measured in uptime, MTTR, and business outcome delivery
- Partnership mentality; we stay invested in the system's success
Proactive monitoring, engineering-led management, and AI application operations, all under one engagement.
Proactive Application Monitoring & Operations
Know about problems before your users do
Production applications degrade in ways that are often invisible until they become incidents, slow queries accumulating, memory leaks growing, third-party dependencies drifting. We deploy observability infrastructure and monitor your application 24/7 with alerting that fires on anomalies, not just outages, so issues are addressed before they affect users or SLAs.
- 24/7 application health monitoring: Uptime, response time, error rate, and business transaction monitoring across all production environments
- Performance trend analysis: Proactive identification of degrading database queries, memory growth, and throughput bottlenecks before they become incidents
- Dependency monitoring: Third-party API availability, database connection pool health, and external service latency tracked continuously
- Alerting and on-call management: PagerDuty, Opsgenie, and Slack-integrated alerting with defined escalation paths and response runbooks
- Monthly operations reports: Application health summary, incident analysis, capacity utilisation, and improvement recommendations delivered monthly
- SLA dashboard: Real-time availability, response time percentiles, and error budget tracking visible to your team at all times
Engineering-Led Application Management
The team that knows your system, keeping it healthy
Application support fails when it is handed to people who did not build the system. We provide ongoing engineering support staffed by engineers who understand your architecture, your business logic, and your edge cases, delivering faster resolution, fewer regressions, and improvement rather than maintenance stasis.
- Bug triage and resolution: Severity-classified defect management with root cause analysis, fix validation, and regression test coverage added for every resolved issue
- Security patching and vulnerability management: Scheduled dependency updates, CVE triage, and emergency patching with zero-downtime deployment strategies
- Performance optimisation: Database query tuning, caching strategy improvements, API response optimisation, and infrastructure rightsizing on an ongoing basis
- Minor feature enhancements: Small capability additions, UI improvements, and workflow adjustments within the managed services engagement scope
- Technical debt management: Structured reduction of code quality issues, dependency updates, and architectural improvements on a defined quarterly roadmap
- Incident management and post-mortems: Structured incident response, root cause analysis, and blameless post-mortems that prevent recurrence
AI Application Operations
Keeping AI-powered systems accurate, safe, and cost-efficient in production
AI-powered applications have operational requirements that traditional application support was not designed for LLM output quality degradation, model drift, hallucination rate changes, and inference cost spirals. We provide managed operations specifically for AI-embedded applications, monitoring AI system health alongside application health.
- LLM output quality monitoring: Automated accuracy, groundedness, and safety scoring with alerts when output quality degrades below defined thresholds
- Prompt regression management: Test suite execution on every model or prompt update to catch quality regressions before they reach production users
- AI inference cost monitoring: Per-call cost tracking, token usage trending, budget alerts, and model routing optimisation to control inference spend
- Hallucination and guardrail monitoring: Output validation pipeline health, guardrail trigger rates, and escalation pattern analysis
- Model drift alerting: Performance metric tracking for embedded ML models with automated notifications when prediction accuracy degrades
- AI incident response: Structured response playbooks for AI-specific failure modes: model unavailability, quality drops, safety violations, and cost spikes
Essential to Enterprise, all tiers staffed by engineers, not ticket processors.
Essential Support
99.5% uptime · 8hr response
Applications requiring reliable monitoring and break-fix support
24/7 uptime and error rate monitoring
Bug triage and resolution (business hours)
Monthly security patching and dependency updates
Monthly health and performance report
Incident response with root cause analysis
Up to 8 hours engineering time per month
Professional Managed
99.9% uptime · 2hr response
Business-critical applications requiring proactive engineering
24/7 monitoring with proactive anomaly detection
Priority bug resolution (4hr SLA for P1 issues)
Continuous security and dependency management
Performance optimisation and technical debt reduction
Minor feature enhancements within scope
Up to 40 hours engineering time per month
Enterprise Managed
99.99% uptime · 30min response
Mission-critical and AI-powered applications requiring full management
Full-stack application and AI system operations
Dedicated engineering team with system context
Unlimited incident response and resolution
Continuous improvement roadmap and quarterly planning
AI output quality monitoring and prompt management
Custom SLA and reporting tailored to your requirements
Clear commitments. Measured outcomes. Monthly reporting on every metric.
| Priority | Definition | Essential | Professional | Enterprise |
|---|---|---|---|---|
| P0 — Critical | Application down, data loss risk, or security breach |
4 hours | 1 hour | 30 minutes |
| P1 — High | Major feature unavailable or severe performance degradation |
8 hours | 2 hour | 1 hour |
| P2 — Medium | Feature degraded but workaround available | 2 business days | 4 hours | 2 hours |
| P3 — Low | Minor issue or enhancement request | 5 business days days | 2 business days | Next sprint |
Healthcare & Clinical Applications
HIPAA-compliant application operations: 24/7 monitoring with PHI-aware alerting, audit logging, and BAA-compliant incident response for clinical and billing applications
RCM platform managed operations: ImpactRCM.AI system health, coding agent accuracy monitoring, denial workflow performance, and AR system reliability management
Clinical AI output monitoring: LLM documentation quality, coding suggestion accuracy, and clinical AI safety threshold monitoring with immediate escalation on degradation
EHR integration health management: FHIR API uptime, message processing error rates, and payer connectivity monitoring across the integration estate
SaaS & Enterprise Applications
Multi-tenant SaaS operations: Per-tenant uptime monitoring, performance isolation, and incident triage across customer environments with transparent status reporting
Enterprise application fleet management: Monitoring, patching, and performance optimisation across a portfolio of internal and customer-facing applications
AI feature operations: LLM quality monitoring, cost management, and continuous improvement for SaaS products with embedded AI capabilities
Post-migration steady state: Managed operations for newly migrated applications during the stabilisation period and beyond
Financial Services Applications
Financial application SLA management: Uptime, latency, and transaction processing rate monitoring meeting regulatory and customer SLA commitments
Compliance: Change management designed to support FFIEC, PCI-DSS and SOX audit trail requirements, with documented approvals, access controls and change traceability.
Trading and risk application operations: Performance-sensitive monitoring and sub-hour incident response for latency-critical financial applications
Security posture management: Continuous vulnerability assessment, patch management, and penetration test remediation for regulated financial applications
99.9%+
Application uptime under managed operations
<1hr
Mean time to restore for P0/P1 incidents
60%
Reduction in incident volume within 6 months
40%
Reduction in infrastructure costs via continuous optimisation
ML is most powerful when connected to the full pipeline
Custom Application Development
Build the application, then transition seamlessly to managed operations at launch
AI-Powered Application Development
AI application engineering, managed post-launch with AI-specific operational coverage.
MLOps & LLMOps
AI model and LLM operations for applications with deep AI system requirements
DevOps, CI/CD & Cloud Infrastructure
The delivery pipeline and cloud infrastructure managed services monitors and maintains.
Tell us what you are running, what matters, and what keeps you up at night. We will match you to the right tier.
We collaborate with global technology leaders to deliver secure and scalable growth-driven digital solutions. Our partnerships strengthen our ability to innovate, accelerate transformation, and drive measurable business impact for our clients.
Top 10 RAG Development Companies in 2026
What happens when your AI sounds confident and gets the facts wrong? It’s a situation many teams are running into. The model responds quickly, the tone is confident, but the facts don’t hold up. And when that happens in a business-critical…
Top Agentic AI Companies in 2026
Agentic AI in 2026 looks very different from what most businesses experimented with just a year or two ago. This is no longer about deploying a chatbot or automating a single task. Agentic AI reasons across goals, makes decisions in context,…
CaliberFocus delivers application support and managed services that help organizations maintain reliable, secure, and continuously improving production systems. From proactive monitoring and engineering-led support to AI application operations, we provide managed services that reduce downtime, improve performance, and keep business-critical applications evolving.
- Proactive monitoring that identifies issues before they impact users
- Engineering-led support focused on reliability and continuous improvement
- AI-aware operations for modern intelligent applications and workflows
- Measurable service outcomes through SLAs, reporting, and optimization
Security & Compliance
