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Retrieval Augmented Generation (RAG)
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Decision Maker
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USE CASE · AI DECISIONING
Decision processes with AI.
Human control when needed.
Approvals, classifications, evaluations, improvement cycles. ARI orchestrates processes where AI decides when it can, and asks the human when it must.
THE PROBLEM
Not all decisions can
be delegated to AI.
AI can handle a large percentage of repetitive decisions: classification, scoring, standard approvals. But there are edge cases, exceptions, high-impact decisions that require human supervision.
Agent-centric frameworks tend to delegate the judgment of when to involve the human to the LLM. This introduces a risk: the agent might fail exactly in the most critical situations. With ARI, the decision logic is explicit and designed by the team.
With ARI: the workflow defines the rules, AI applies, the system records, the human intervenes only when necessary.
01
Risk of unsupervised AI
An autonomous LLM agent might decide not to involve the human exactly when it would be necessary. The threshold is opaque. ARI thresholds are explicit.
02
Regulation and audit trail
In regulated contexts (banks, insurance, gov), every decision must be justified and traced. ARI produces complete logs: who decided, when, why.
03
Progressive improvement
Every case where a human corrects the AI is a valuable signal. ARI's Research Tree tracks these feedbacks to refine rules over time and reduce Human In The Loop cases.
HOW IT WORKS
The decision flow
with selective supervision.
Case Reception
The workflow receives the input: a file to evaluate, a document to classify, a request to approve or content to moderate.
Decision Maker Analysis
The Decision Maker node analyzes the case and makes a decision: documenting the logical path and the information considered.
Conditional Routing
If confidence exceeds the threshold, the workflow proceeds. If below, or if the logic requires it, the system activates the Human In The Loop node.
Human In The Loop: Human Review
The Human In The Loop node sends the review request to the operator. The operator sees the case, the proposed decision and the reasoning to decide.
Feedback Loop
Human overrides are tracked in the Research Tree. Over time, this dataset allows refining decision rules and reducing Human In The Loop cases.
BUILDING BLOCKS USED
The components of this workflow.
01
Decision Maker
Analysis, evaluation and decision with complete traceability of reasoning and explicit confidence scoring.
02
Human In The Loop: Human-In-The-Loop
Selective human supervision and approval management with full contextual information for the operator.
03
RAG / Knowledge Manager
Retrieval of policies and decision rules from document bases. The Decision Maker follows company rules, it doesn't invent them.
04
Research Tree
Tracking of experiments and feedback for continuous improvement. Human In The Loop cases become training data for future refinement.
EXPECTED RESULTS
What you get in production.
80-90%
Auto-resolved cases
Standard cases handled without human intervention.
−60%
Processing time
Reduction in average time per case compared to manual flows.
100%
Audit trail
Every decision is traced: who, when, why, AI or human.
APPLICATION SECTORS
Who uses Agentic Workflows on ARI.
SETTORE 01
Insurance
Automatic underwriting with edge case supervision. Claims scoring and routing to the right human liquidator.
SETTORE 02
Banking and Fintech
Credit scoring, loan approvals and KYC. The Decision Maker applies policies and Human In The Loop covers borderline cases.
SETTORE 03
Legal and Compliance
Classification of legal documents, contract compliance verification and triage with traceable reasoning.
SETTORE 04
HR and Public Admin
Initial screening of candidates and classification of support tickets. Automatic investigation with mandatory legal supervision.
Do you have a decision process to automate with supervision?
Show us your concrete case. In 30 minutes we will understand together if and how ARI can bring it to production reliably.
ARI is the private operational automation suite for enterprises: build your own custom AI workflows, or start right away with ready-to-use vertical products.
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