Case Studies

Government Legal Intelligent Agent Platform

Large Government Legal Review Agency

This government legal agency adopted FIM One to run a legal agent platform, breaking through LLM long-text "forgetting" issues to deliver intelligent pre-review and risk control for complex legal texts.

AI
Key Metrics

Business Impact

0%
Efficiency Increase
Average processing time per case file significantly reduced
0%
Context Integrity
Ensuring no key constraints are missed in long-case reasoning
0%
Expert Adoption
Percentage of AI-generated suggestions accepted by legal experts
Full
Traceability
Full evidence chain provided for every reasoning step
Core Technology Features

Technical Highlights

FIM One Dual-Track

Workflow ensures compliance while Planner handles autonomous judgment, deeply fitting complex scenarios

Verbatim Grounding

AI conclusions are strictly anchored to original text clauses for full traceability, addressing the "forgetting" issue

Intelligent Provenance

Problem-Basis-Logic-Conclusion: full chain explainability, rejecting black-box operations

Three-layer Knowledge Arch

Global/Org/Tenant isolation, achieving "default isolation, on-demand sharing"

Full100+AI1000+
Adoption Overview

Customer Context

This large government legal agency handles a massive volume of complex legal texts and compliance documents. The traditional manual mode faced challenges of long case files and multiple compliance dimensions (hundreds of rules). Early attempts with generic LLMs were limited by context windows and hallucination issues, failing to handle extra-long files with the necessary explainability for rigorous compliance.

Technology Stack

FIM OneContext EngineeringKnowledge GraphRAG Architecture
Transformation

From Pain Points to Adoption

Transformation
1Long-text information decay: Complex cases often span hundreds of pages, and models tend to forget key constraints after multiple turns, leading to contradictory conclusions
Ran on the FIM One framework, using its "Workflow (deterministic) + Planner (autonomous)" hybrid scheduling to balance compliance and flexibility
2Black-box reasoning distrust: End-to-end generative AI lacks intermediate reasoning processes, making it hard for experts to judge the basis of conclusions
Turned on the Context Engineering Engine with "Verbatim Grounding" strategy to solve recursive information decay and ensure long-chain reasoning consistency
3Knowledge permission management: Different departments have both shared standards and internal rules, making it difficult for traditional knowledge bases to isolate data
Used FIM One to set up a Multi-tenant Three-layer Knowledge Architecture for "Global Shared - Org Private - Tenant Isolated" management with automatic inheritance
4Inflexible workflows: Simple workflows cannot handle complex logical judgments, while pure Agent planning can easily spiral out of control
Leveraged FIM One's Intelligent Provenance Evidence Chain to output a "Problem - Compliance Basis - Logic - Conclusion" loop that significantly raised expert adoption
Technical Architecture

System Architecture Design

Layer 1
Knowledge Service Layer

Innovative 3-tier knowledge architecture (Global/Org/Tenant) enabling 'default isolation, scalable sharing'

Global SharedOrg PrivateTenant IsolationInheritance
Layer 2
Agent Synergy Layer (Agent SDK)

Context-driven Agent SDK supporting dual-track scheduling: Workflow (Deterministic) + Planner (Autonomous)

Dual-TrackContext EngVerbatim GroundingHot-Swap Skills
Layer 3
Intelligent Application Layer

Business-oriented Agent Matrix covering intelligent pre-check and full lifecycle risk control of complex legal texts

Normative Pre-checkDeep Risk AnalysisTerm ConsistencyTraceability
复杂文档入湖Agent 自主协同长文本研判对标Verbatim Grounding
Adoption Journey

Phased Implementation

1
Evaluation

Core Foundation

The agency rolled out FIM One, set up the three-layer knowledge architecture, and curated high-quality legal evaluation datasets

2
Pilot

Agent Swarm Pilot

The agency configured agents for regulatory pre-review, deep risk control, and clause consistency, then tuned RAG retrieval performance

3
Scale-out

Multi-agency Scale-out

The agency extended FIM One to subordinate units; expert evaluation confirmed significant overall processing efficiency gains

Testimonial

Customer Voice

Previously, reviewing a complex case took days of cross-referencing hundreds of clauses. Now, the AI agent provides a complete reasoning chain with verbatim grounding, reducing our workload significantly while maintaining rigor.

Legal Review Division Director

Senior Legal Expert

FAQ

Frequently Asked Questions

How does the system solve the "forgetting" problem in long texts?
Can we trust the AI's legal conclusions?
How are internal rules and public standards separated?
Does the system support complex logic or just simple search?

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