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The platform does more than locate documents. It can:
Facthory complements your existing systems by creating an intelligence and reasoning layer across them.
Read about the Living Operational Model or contact our team to discuss your current technology landscape.
Unlike a static knowledge base, the model evolves as new information becomes available. It can incorporate operational documents, enterprise-system records, communications, videos, decisions, procedures, project activity, and expert contributions.
This gives AI agents the context required to understand not only what information exists, but also:
Learn more about the Living Operational Model.
Depending on your environment and deployment, sources may include:
Connections can be established through supported integrations, APIs, secure file ingestion, or purpose-built connectors.
Explore Systems and Data Connectivity or contact us about an integration.
Your ERP remains the system of record for operational transactions. Your document platform continues to manage files. Your data platform retains analytical datasets, and your collaboration tools continue to support communication.
Facthory provides the contextual layer above these systems. It connects fragmented information, models operational relationships, and enables AI agents to reason and work across organizational boundaries without requiring a disruptive replacement program.
Read about our enterprise integrations or book an architecture discussion.
Typical stakeholders include:
Facthory can begin with a focused departmental use case and expand into a shared operational intelligence layer across the enterprise.
Explore our solutions or talk to an expert.
Rather than asking a general-purpose model to answer from its pretraining alone, Facthory can retrieve relevant enterprise context, evaluate source quality, identify conflicting information, and require evidence for important claims.
For higher-risk use cases, organizations can introduce:
No AI system can guarantee that every generated statement will always be correct. Facthory is therefore designed to make uncertainty visible and to place appropriate controls around consequential outputs.
Read about Operational Graph and Search and Research and Technical Reasoning.
A deployment may use supported commercial models, privately hosted models, open-weight models, or a controlled combination of models for different tasks. For example, one model may handle high-volume extraction while another is reserved for complex engineering or scientific reasoning.
Model selection can be governed by:
Discuss your preferred model and hosting strategy through an AI architecture consultation.
Relevant capabilities can include:
Facthory can also be configured so that sensitive customer information remains within an approved cloud region or private environment and is not used to train external foundation models.
Review Security, Governance and Compliance or contact our security team.
Depending on the deployed use case and associated risk classification, these controls may include:
The EU AI Act applies differently depending on the system, intended purpose, users, and risk level. Facthory does not replace legal assessment, but it can provide the governance infrastructure required to manage enterprise AI systems more systematically.
Read about AI Governance and Compliance or request an EU AI Act workshop.
Available controls may include:
The final security architecture depends on your selected deployment model and integration landscape.
Explore Security, Governance and Compliance or request our security documentation.
Depending on the project requirements, Facthory can be deployed through:
Private deployments can provide greater control over networking, data location, model hosting, identity, monitoring, and integration with internal systems.
Read about Private Cloud and On-Premises Deployment or book a deployment assessment.
Storage location, retention, processing region, model access, and backup arrangements depend on the agreed deployment architecture. Enterprise customers can define requirements relating to:
These requirements are reviewed during solution design and documented as part of the deployment.
For a detailed assessment, contact our enterprise team.
Durable research agents can investigate technical questions across internal and external sources, maintain a research plan, compare competing evidence, identify unanswered questions, and produce structured research artifacts.
Use cases may include:
Researchers remain able to inspect sources, challenge assumptions, refine the investigation, and approve final conclusions.
Read about Scientific Research and Experimental Intelligence.
Rather than requiring users to define every dashboard or query in advance, agents can:
Access to data and analytical actions remains governed by organizational permissions and approved execution environments.
Explore Autonomous Analytics and Insight Discovery or book an analytics demonstration.
The platform can identify role-level and organizational skill gaps, then create adaptive learning paths using approved internal knowledge and external training material.
Capabilities can include:
This allows learning programs to reflect how work is actually performed rather than relying only on generic course catalogues.
Read about Workforce Readiness and Adaptive Learning.
The goal is to understand organizational dependencies and improve knowledge resilience - not to create automated employee-performance judgments.
Your team can review, correct and extend the discovered structure, combining automated discovery with organizational governance.
Facthory also considers which processes, assets, teams and outcomes depend on the knowledge so that risks can be prioritized according to business impact.
Organizations can maintain common enterprise domains while allowing site- or department-specific knowledge and practices.
People remain responsible for validating critical findings, approving organizational knowledge and making consequential workforce or operational decisions.
This allows agents to use organizational knowledge more reliably while preserving source traceability and human approval requirements.
It can help identify:
The result is not merely a static process diagram. Facthory can connect the discovered process to responsible people, supporting evidence, systems, performance indicators, and improvement initiatives.
Read about Process Discovery and Continuous Optimization.
With appropriate authorization and governance, the platform can identify:
Facthory also supports expert escalation, question routing, project coordination, scheduling, and agent-assisted follow-up without requiring every discussion to move into a new application.
Explore Expert Collaboration and Communication Intelligence.
Potential use cases include:
The purpose is not to replace financial systems, but to provide a reasoning and investigation layer across the information required for better enterprise decisions.
Read about Enterprise Performance, Risk and Control Intelligence or schedule a CFO-focused discussion.
Capabilities can include:
Findings can be linked to the supporting records, responsible teams, affected procedures, and recommended actions.
Read about Manufacturing Quality and Reliability Intelligence.
Depending on the use case and video quality, the platform can identify and extract:
Video intelligence can be combined with documents, system records, images, and expert review to create a more complete understanding of operational work.
Explore Video-Based Operational Intelligence or book a video-analysis demonstration.
Use cases may include:
The platform can work alongside ERP, procurement, contract-management, and supply-chain systems rather than requiring those systems to be replaced.
Read about Procurement and Supply Chain Intelligence.
Your ERP, MES, QMS, CMMS and PLM remain authoritative systems of record. Facthory provides the contextual and reasoning layer that allows people and agents to investigate and coordinate work across them.
A manufacturer can establish shared enterprise taxonomies and agent capabilities while preserving site-specific procedures, terminology, systems and permissions.
Analytical agents can explore datasets, identify anomalies, test hypotheses and explain findings in the context of relevant assets, processes and decisions.
The appropriate architecture depends on your data residency, model hosting, network, identity and regulatory requirements.
Experts can inspect evidence, correct assumptions, redirect agents and approve consequential findings, procedures or actions. Facthory preserves those reviews as part of the operational record.
Translation can be combined with expert validation and governed publication for safety- or quality-critical content.
Organizations can define:
This allows organizations to establish common standards without removing the local context required by individual operations.
Discuss your rollout strategy through an enterprise platform consultation.
An initial discovery phase can determine:
Facthory can progressively improve the quality and structure of the operational model as additional sources and feedback become available.
Good initial use cases often have:
Facthory can then establish the necessary context, integrations, governance, and agent capabilities around that use case before expanding into a broader operational intelligence program.
Explore our solutions, book a demonstration, or contact sales.
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