Facthory treats technical work as an investigation, not a prompt-response exchange.
Turn broad questions into explicit assumptions, subproblems, constraints and success criteria.
Problem decomposition
Assumptions
Constraints
Success criteria
A technical answer may depend simultaneously on a journal article, internal test result, maintenance history, engineering drawing, patent, supplier specification and expert observation. Facthory brings those sources into one investigation while preserving where every claim came from and which evidence supports or contradicts it.
Find, compare and synthesize relevant scientific and technical publications around a specific engineering question.
Investigate patents, claims, prior art and technical novelty alongside internal product and R&D context.
Reason against specifications, standards, requirements and constraints instead of treating them as detached documents.
Generate competing explanations, identify discriminating evidence and test which explanation best fits the facts.
Use calculations, code and analytical tools when a technical question cannot be answered from text alone.
Compare conflicting sources, expose contradictions and distinguish established evidence from assumption or inference.
A difficult engineering problem should not be handed to one general-purpose agent. Facthory can divide the investigation among specialized agents for literature, patents, internal evidence, data analysis, calculations and standards. Their findings return to a shared investigation where contradictions can be challenged and missing evidence assigned back out. People can enter the same session, correct assumptions, add domain knowledge and approve the final conclusion. The result is one coherent technical record rather than disconnected AI outputs.
Search internal and external sources while maintaining provenance and source quality.
Seek contradictory evidence, run analyses and identify where the current explanation can fail.
Escalate uncertain assumptions and consequential conclusions to the right technical reviewers.
Retain evidence, calculations, decisions and corrections as enterprise technical memory.
For scientific and engineering work, fluency is not enough. Facthory separates source evidence, model inference and human judgment so teams can inspect why a conclusion was reached, where uncertainty remains and which assumptions should be tested next.
Keep findings tied to the documents, data, calculations and tools that produced them.
Surface assumptions, contradictions and unresolved questions instead of hiding them behind confident language.
Route consequential findings to designated engineers, scientists or domain owners before operational use.
Apply the same investigation infrastructure across different scientific and engineering disciplines.
Investigate hypotheses, prior work, experiments and technical alternatives with shared evidence.
Evaluate designs, requirements, trade-offs, failures and technical decisions against operational evidence.
Investigate defects, deviations and root causes using evidence across product and process history.
Connect failure history, maintenance evidence and technical literature to investigate recurring problems.
A strong technical investigation should become reusable organizational intelligence. Facthory preserves the question, evidence, rejected hypotheses, calculations, expert corrections and final decision instead of allowing that reasoning to disappear into a report or private AI session. Future teams and agents can begin from what was already established, revisit conclusions when new evidence appears and understand why an earlier technical decision was made.
The goal is not faster answers. It is stronger scientific and engineering decisions built on evidence that can be challenged.
Define the decision, technical question, assumptions, constraints and required standard of evidence.
Gather internal and external evidence using specialized agents working in parallel.
Run calculations, analyses and tool-assisted checks against the strongest competing explanations.
Bring experts into the shared investigation to challenge evidence, assumptions and conclusions.
Preserve the conclusion, confidence, evidence and unresolved questions as reusable technical memory.
Break complex questions into explicit technical subproblems that can be investigated independently.
Persist work across hours or days without losing plans, evidence, intermediate findings or review state.
Use code, calculations, data analysis and connected technical tools as part of the reasoning process.
Identify where evidence conflicts instead of collapsing disagreement into a single synthetic answer.
Make assumptions explicit and retain which conclusions depend on them.
Trace claims back to their internal records, external sources, calculations and tool outputs.
Represent unresolved questions and confidence instead of forcing certainty where evidence is incomplete.
Invite scientists and engineers directly into investigations to add evidence, challenge reasoning and approve conclusions.
Facthory separates research, analysis and recommendation from consequential action. Agents operate with scoped data access and approved tools, while evidence, tool calls and human interventions remain traceable. Teams can require expert approval before findings influence engineering changes, experiments, procurement decisions or operational workflows.
Scientific and engineering teams face growing evidence, investment and AI adoption while decisions still require expert judgment.
of OECD R&D is business-led
patent applications filed worldwide
annual growth in patent filings
researchers surveyed on AI use
Bring one complex scientific or engineering question. Facthory can connect the relevant enterprise context, external evidence and specialist agents into a governed investigation your experts can inspect and continue.
