Product Advantage
TheFedGPTAdvantage
FullyOn-PremisesDeployment,FullAISovereignty
FedGPT provides an enterprise-grade, fully on-premises Agentic AI platform. Users can build their own RAG knowledge base, run fine-tuning, and design Agentic application workflows entirely on-site. Free from cloud service constraints, enterprises can flexibly scale AI use cases according to their own data, processes, and governance requirements, ensuring full control over security, sovereignty, and platform direction, and building a core operational capability they can control for the long term.
InternationalSecurityStandards,GDPR&EUAIActCompliant
FedGPT is trained using federated learning, with data governance principles aligned with international compliance standards such as the EU GDPR and AI Act. Its built-in Guardian mechanism filters out discriminatory or biased language and helps avoid ideological skew, outperforming general-purpose LLMs in bias testing.
AIExpertTeamWorkflow,AutomatedTaskCompletion
Through visual Flow design, AI handles queries, aggregation, decision support, and process execution, forming an "expert team" that automatically completes complex, multi-step tasks. This frees up productivity, cuts routine work hours by 40%, and elevates FedGPT from a single-point tool to a long-running enterprise process engine.
ACustomEnterpriseBrainThatUnderstandsYourContextInstantly
As an enterprise-grade multimodal platform, FedGPT supports building a dedicated knowledge base from text, images, and audio, centralizing scattered internal documents and information. Through RAG and application-layer tuning, the AI accurately recognizes names, industry terminology, and proper nouns, helping employees quickly access the right information and making enterprise knowledge truly understandable, usable, and enduring.
SeamlessIntegrationwithExistingWorkflows,InstantProductivityGains
FedGPT natively supports APIs and MCP integration with common enterprise tools such as Google and Microsoft, letting AI work within existing workflows. Enterprises can significantly shorten the transition period and lower the cost of AI adoption, all while maintaining full control over on-premises data.
LowPower,HighPerformance,SustainableEnterpriseAI
Developed by a dedicated algorithm engineering team using proprietary LLM optimization techniques, FedGPT's inference cost is about 30% that of large-scale models, delivering stable performance while reducing compute and energy consumption. Compared to resource-intensive model architectures, FedGPT achieves more with less, balancing performance, operational cost, and sustainable AI goals.
Scenario
FedGPTUseCases
Government/Education—StreamliningAdministrativeWork
Built on knowledge base upload, classification, and access control, FedGPT integrates official documents, regulations, and SOPs. It supports Agentic RAG, which first determines whether a knowledge source is needed before producing a traceable response, and can combine with Flow to break multi-step administrative processes into stages, taking staff from "looking up information" to "drafting documents and guiding next steps."
。Faster administrative processing: Uses RAG to retrieve existing official document templates, producing draft documents with cited sources.
。Instant regulation Q&A: Uses FAQs for consistent, standardized answers to regulatory questions.
。Case routing: Flow branches by condition to automatically classify applications from citizens or schools and flag the documents needed for the next step.
FinancialServices—AcceleratingFinancialOperations
FedGPT uses node-based Flow orchestration to connect multi-step financial processes, calling internal and external systems via API and MCP. RAG retrieval brings internal policies, operating manuals, and form rules directly into responses, enabling staff to cross-check data, verify rules, and consolidate results, all while maintaining a traceable, auditable operational record.
。KYC: RAG retrieves internal policy while Flow assembles a checklist, flagging missing items and risk points.
。Compliance clause comparison: Compares internal policy clauses against the latest regulatory interpretations, producing a summary of differences and action items.
。Consistent ticket and customer service responses: Uses FAQs for high-frequency questions, ensuring consistent answers across staff.
Healthcare—ReducingAdministrativeBurden
FedGPT addresses the overload of hospital administrative work by using RAG to integrate institutional policies, processes, forms, and operating guidelines, with access control separating data visible to different roles. Multi-step task assignment and approval are handled through Flow, allowing AI to provide consistent process guidance, document consolidation, and regulatory lookups.
。Hospital SOP lookup: RAG retrieves SOPs with citations, producing steps and key considerations.
。Form and process guidance: Flow branches by scenario with human input, producing forms and the corresponding approval path.
。Standardized compliance: A fixed FAQ set combined with RAG produces consistent answers with clause citations.
Film,Audio,andMedia—FasterContentProduction
FedGPT's advanced modules combine asset management with multimodal analysis: video and image analysis produce searchable content leads, and an asset library builds recognizable content tags. Combined with RAG, script archives, interview notes, and style guidelines are brought into retrieval, taking staff from "finding assets" to "summarizing key points and generating a first draft" in a reusable content workflow.
。Video logging: VLM analyzes video footage combined with an asset library, producing searchable scene descriptions.
。Finding people and footage: Facial recognition combined with an asset library and retrieval, producing timestamped locations of a person's appearances.
。Interview summarization and topic screening: ASR transcription combined with RAG database retrieval and classification rules, producing topic context and key takeaways.