What we
build

Four practices, one operating model. We take AI from idea to production and keep it running.

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01 / STRATEGY
AI Strategy & Readiness
Assessments, roadmaps, use-case prioritization, and build-vs-buy decisions.
02 / SYSTEMS
Custom AI Systems
LLM applications, AI agents, RAG pipelines, and bespoke ML models.
03 / INTEGRATION
AI Integration & Automation
Workflow automation, legacy system integration, and API orchestration.
04 / GOVERNANCE
AI Governance & Operations
Security review, compliance, model monitoring, and managed AI ops.
hello@apls.ai SOC 2 · ISO 27001 · Data residency on request
CS.01 Work — Financial Services

The claims queue, governed.

A national insurer replaced a manual claims review queue with a governed AI agent — every decision logged, every exception escalated to a human adjudicator.

Sector
FINANCIAL SERVICES
System
AI AGENT + RAG
Timeline
11 WEEKS TO PRODUCTION
01 / CHALLENGE

A queue measured in weeks.

Claims arrived faster than adjudicators could review them. Routine claims — the clear majority — consumed the same senior attention as genuinely contested ones. Backlog grew, cycle time stretched, and the cost of review scaled linearly with volume.

A previous automation pilot had stalled in security review: no audit trail, no escalation design, no answer to "who is accountable for a denial."

02 / APPROACH

Bounded autonomy, by design.

We started from the accountability question, not the model. The agent was given explicit authority boundaries: it can approve routine claims within policy terms; it can draft determinations; it cannot deny. Every denial path routes to a human adjudicator with the agent's full reasoning attached.

Policy documents were indexed into a permission-aware retrieval layer so every determination cites the exact clause it relies on.

03 / ARCHITECTURE

Four components, one audit trail.

Intake parses and classifies the claim. The policy RAG layer retrieves the controlling terms. The agent drafts the determination with citations. The review console routes exceptions and records the human decision. All four write to a single immutable log.

FIG. 01 — AGENT TOPOLOGY
04 / OUTCOME

Faster, and defensible.

Within one quarter of cutover, routine claims cleared in hours instead of days, contested claims reached senior adjudicators sooner, and audit had a complete decision trail for the first time.

62%
reduction in average handling time
0
unreviewed denials, by construction
94%
of routine claims resolved within SLA
100%
of determinations carry policy citations

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