Helping enterprises with AI — and the people behind it
Four composable service lines — specialized AI talent, cloud-native engineering, autonomous operations, and enterprise consulting — delivered with governance and observability from day one.
Native integrations across the enterprise stack
Four service lines. One partner for enterprise AI.
From specialized talent and production engineering to autonomous operations and strategic consulting — composable, governed, and observable end-to-end.
AI Staffing & Talent
Pain · Scaling AI initiatives without specialized engineering depth.
Outcome · Embedded ML, MLOps, and AI infrastructure engineers in days, not quarters.
AI Development & Engineering
Pain · PoCs that never reach production due to weak infrastructure.
Outcome · Cloud-native AI systems, RAG pipelines, and agentic workflows engineered for scale.
Autonomous AI Operations
Pain · Alert fatigue, manual triage, and operational toil at scale.
Outcome · Governed autonomous remediation across infrastructure, security, and cost.
IT Consulting & Digital Transformation
Pain · AI ambition without a clear roadmap to enterprise outcomes.
Outcome · Strategy, architecture, governance, and change delivered by Fortune 500 veterans.
Why enterprise AI stalls between PoC and production.
The gap isn't model quality — it's the operational substrate. Infrastructure, observability, and governance are what turn experiments into outcomes.
- Weak infrastructureCobbled-together inference paths with no SLOs.
- Poor observabilityBlack-box models with no signal into latency, drift, or cost.
- Governance gapsNo policy gates, audit trails, or approval workflows.
- Unreliable deploymentManual promotions, no canaries, no rollback.
- Scaling complexityVertical pilots that can't horizontalize across the org.
- Operational fragmentationDisjoint tooling across data, ML, infra, and security.
Signal → Analysis → Approval → Action
A continuous loop that observes infrastructure, reasons over telemetry, applies governance, and executes remediations — with humans in the loop where it matters.
OTel-native ingestion across logs, traces, metrics, events.
LLM + classical models correlate anomalies and infer causes.
OPA-based gates, approval workflows, change-window awareness.
Idempotent executors with rollback and full audit trail.
Operational AI agents, production-tested.
Pre-built, governed agents that target the highest-cost operational toil — deployable into your existing stack.
Incident Triage Agent
Mean-time-to-detect bottlenecks across noisy telemetry.
SRE Automation Agent
Repetitive runbooks consuming on-call cycles.
Certificate Rotation Agent
Expired TLS certs causing production outages.
Cost Optimization Agent
Cloud spend drift across multi-account estates.
Compliance Agent
Continuous control evidence for SOC 2, ISO, HIPAA.
Network Operations Agent
Multi-cloud network topology and policy drift.
Deployed across regulated, latency-sensitive enterprises.
Financial Services
Fraud telemetry, model risk governance, low-latency inference.
Healthcare
HIPAA-aligned RAG, clinical workflow agents, audit-ready AI.
SaaS & Technology
AI feature platforms, observability copilots, autonomous SRE.
Enterprise IT
ITSM automation, incident triage, compliance evidence.
Retail & E-Commerce
Demand forecasting agents, catalog enrichment, ops automation.
A structured path from intent to production.
Risk-reduced delivery with measurable milestones at each gate.
Discover
Map systems, telemetry, risks, and the production gap.
Design
Reference architecture with governance and observability.
Build
Engineer cloud-native AI services with SLOs from day one.
Deploy
Progressive rollout with policy gates and approval workflows.
Optimize
Continuous tuning across cost, accuracy, and latency.
Helping Enterprises With AI and People
From AI talent and cloud-native engineering to autonomous operations and enterprise consulting, DevAppsIT helps you move from ambition to measurable production outcomes.