Facthory preserves what each modality knows, then connects the meaning across them.
Ingest structured and unstructured data from enterprise systems, repositories, people and the physical environment.
Databases and APIs
Documents and email
Video and audio
Sensors and events
Facthory can treat video as a time-based source of knowledge: speech, frames, objects, actions, sequence, environment, on-screen text and visible machine state. Those observations can be linked to the relevant asset, work order, procedure and later outcome instead of being buried inside a media file.
Parse manuals, SOPs, PDFs, presentations, spreadsheets, emails and collaboration content while preserving structure and metadata.
Connect ERP, MES, CMMS, CRM, lakehouse and operational systems so records stay tied to real entities and events.
Interpret demonstrations, inspections, incidents and field footage as sequences of actions, objects, states and evidence.
Turn interviews, calls, shift handovers and expert explanations into attributed, searchable knowledge with timestamps and context.
Align time-series signals, alarms, machine states and events with the human actions and evidence surrounding them.
Understand photographs, diagrams, scans, drawings and visual defects as part of the same operational story.
A compressor fault can exist simultaneously as a sensor spike, an alarm, a work order, a technician voice note, a thermal image, a maintenance video and an SOP. Most platforms index these separately. Facthory aligns them around the same asset, event and time window. The result is not seven searchable objects. It is one evidence-linked representation of what happened, what people observed, what the system recorded, what procedure applied and what fixed it. That fused context becomes reusable for the next investigation, agent plan or human decision.
Route content through document, vision, speech, video, table and time-series intelligence.
Synchronize records, frames, transcripts and telemetry around the same operational moment.
Link people, assets, parts, locations, processes and events across incompatible systems and names.
Make fused context retrievable, traceable and reusable by authorized people and agents.
A PDF, a waveform, a video stream and a database row do not carry meaning the same way. Facthory routes each source through the right extraction and reasoning path, then reconciles the outputs against shared enterprise context.
Choose the right parsing, vision, speech, retrieval or reasoning path for each source instead of flattening everything into plain text.
Keep extracted facts connected to the page, frame, timestamp, record or signal from which they came.
Compare what systems recorded with what people said and what cameras or sensors observed to surface conflicts and strengthen confidence.
Facthory captures knowledge at the moment it is created, not months later in a documentation project.
Capture decisions, exceptions and handovers while work is being performed.
Pair machine state and telemetry with what operators see, hear and do.
Record mobile video, voice and images where physical work actually happens.
Activate the years of documents, databases and media the enterprise already owns.
Multimodal knowledge capture is not a file-upload feature. The goal is to build a faithful machine-readable representation of operations. If the same incident appears in a database row, camera footage, a voice explanation and a sensor trace, those are not four documents. They are four observations of one event. Facthory preserves the differences between those observations, connects them through shared entities and time, and turns them into memory the enterprise can reuse. That is how a data estate becomes a living brain.
The enterprise already has the data. The advantage comes from connecting what every source knows before the context disappears.
Start with one operational problem where valuable context is spread across multiple sources and modalities.
Connect the authoritative systems, repositories and data platforms already used by the business.
Add video, voice, image or edge capture where critical knowledge is created outside existing systems.
Resolve entities, align timelines and connect evidence into reusable operational context.
Reuse the ingestion, governance and memory layer across additional teams, sites and use cases.
Preserve headings, tables, figures, references and page structure so retrieved knowledge retains document meaning.
Interpret rows, columns, keys and business semantics from spreadsheets, exports, databases and analytical models.
Break long recordings into meaningful scenes, actions and evidence windows without treating every frame equally.
Transcribe multilingual audio, preserve timing and distinguish speakers so explanations remain attributable and searchable.
Read labels, screens, diagrams, scans and technical imagery while connecting extracted text to surrounding visual evidence.
Synchronize telemetry, alarms and state changes with media, records and human observations around the same time window.
Recognize when different sources refer to the same asset, person, process, part, location or incident.
Keep source lineage, timestamps and evidence boundaries attached to derived knowledge so conclusions can be inspected.
Multimodal AI becomes dangerous when extraction severs knowledge from its origin. Facthory keeps derived context tied to source records, timestamps, pages, frames, speakers and access boundaries. Authorized users and agents can trace an answer back to the evidence, distinguish observed facts from generated interpretation and route uncertainty to human review.
The opportunity is not another chatbot over documents. It is converting data already generated by people, systems and the physical world into reliable machine context.
of enterprise data is unstructured
is directly ready for AI consumption
connected IoT devices in 2025
Start with one high-value workflow. Facthory connects the systems, documents, media and physical signals around it, then builds the governed context your teams and AI agents can reuse everywhere.
