Production AI. Shipped.
Most enterprise AI dies between pilot and production. APLS is the partner that ships it — with security, governance, and measurable ROI engineered in from the first week.
Pilot purgatory is where AI goes to die.
Most enterprise AI never leaves the lab. A proof of concept impresses a steering committee, then stalls — blocked by security review, missing data pipelines, and no clear owner for the model in production.
The gap is not ambition. It is the distance between a notebook that works once and a system that runs every day, under load, with auditable behavior and a budget line attached.
We close that gap. APLS designs, builds, and operates AI systems that survive contact with real users, real compliance, and real scale.
Four practices. One operating model.
Readiness
Know which use cases pay back, which to retire, and whether to build or buy — before you spend.
Assessments · Roadmaps · Prioritization → 01Systems
LLM applications, AI agents, and RAG pipelines that ship — tested, documented, and owned.
LLM apps · Agents · RAG · ML → 02Automation
Wire AI into the systems your business already runs — legacy stacks, APIs, and workflows.
Workflow · Legacy · Orchestration → 03Operations
Monitored, compliant, and accountable in production — security review through managed AI ops.
Compliance · Monitoring · Managed ops → 04Assess. Architect. Build. Scale. Govern.
We inventory every candidate use case and score it on value, feasibility, and risk — so the roadmap starts from evidence, not enthusiasm.
→ Deliverable: AI Readiness ReportA reference architecture, data flow, and explicit build-vs-buy decision for every component — reviewed with your security and platform teams.
→ Deliverable: Solution BlueprintWe ship in 4–8 week delivery cycles — production code, evaluation harnesses, and documentation, not a demo that breaks on the second prompt.
→ Deliverable: Production SystemLoad, cost, and adoption hardened for the whole organization — with rollout sequencing and the cost-per-outcome modeled before you commit.
→ Deliverable: Rollout PlanMonitoring, evaluation, and compliance you can hand to audit — drift, behavior, and spend tracked with immutable logs from day one.
→ Deliverable: Operations RunbookReport
Blueprint
System
Plan
Runbook
Outcomes, not output.
A claims operations team replaced a manual review queue with a governed AI agent — every decision logged, every exception escalated to a human.
Built to pass the security review.
Enterprise buyers read this section twice. So we lead with it: security posture, compliance, and model operations are part of the build — not a document produced after the fact.
Deploy in your cloud, your region, your controls. Every model is evaluated before and after release, monitored in production, and accountable to audit.
Tell us where your AI initiative is stuck. We will respond within one business day with a point of view — not a pitch deck.
Message received.
We respond within one business day — usually with a question, not a quote. Talk soon.