Open cognitive infrastructure
Know where an answer came from. Rosetta connects claims to their sources, context, and history—so people and AI systems can reason with evidence that remains open to inspection.
So they CLAIM...? We keep receipts.
Every conclusion has a history.
A laboratory report records a sample temperature of 21 °C.
The original record anchors the chain. A receipt can identify the artifact, its author, and the time it was recorded.
Inside the receipt
Example record · LAB-001
The recorded temperature is within the stated 20–22 °C range.
An observation describes what the record supports. It retains the measurement context and does not silently become a broader claim.
Inside the receipt
Derived from · LAB-001
This reading is consistent with the stated storage condition.
An interpretation adds reasoning. Its assumptions and limitations belong beside the claim: one reading does not establish continuous compliance.
Inside the receipt
Assumption · Sensor reading is accurate
Further readings could help establish whether the condition persists.
A projection concerns what may follow. It is conditional, and later evidence can revise it without erasing the earlier reasoning.
Inside the receipt
Uncertainty · Future conditions are unknown
Research & perspectives
Evidence reviews and research proposals on auditable intelligence, technological change, and the institutions that must adapt.
A technical proposition for a shared physical-context exchange across spatial twins, embodied AI, XR, robotics, live performance, simulation, and receiver-side reconstruction.
Persistent agent memory is state-transition machinery: evidence, projections, activation, context, procedures, authority, lifecycle, revalidation, and recovery must remain distinct and governed.
OMoC treats reasoning as a semantically routed computation graph: task-local concept signatures select heterogeneous cognitive operators instead of static agent roles.
How Entif works
A research, verification and collaboration layer for an open intelligence ecosystem. Evidence and interpretation stay distinct so reasoning can be challenged and corrected.
Questions, methods and results that remain open to scrutiny.
Follow claims back to evidence, context and competing interpretations.
Build portable semantic infrastructure that systems can inspect and reuse.
Keep authority, accountability and correction in human hands.
Our approach
Open standards. Explicit uncertainty. Evidence that survives the handoff.
Entif AI is being organized toward a public-benefit foundation model for intelligence that can be inspected, challenged, corrected, and improved. We connect technical questions about meaning, memory, learning, orchestration, and world interaction to institutional questions about evidence, authority, consent, accountability, and who benefits when capability increases.
An answer is more useful when you can inspect its sources, distinguish observation from interpretation, understand which transformation produced it, and see what has to change if an upstream premise is corrected. Rosetta provides the public semantic and provenance foundation for that work.
Bilqis, Codito, Akasha, GNOSIS, OMoC, Swarm Gnosis, and IndraNet explore a complementary question: can successful cognition become durable structure instead of being rented again from a general model every time the same problem reappears?
The goal is not one giant synthetic mind. It is a system in which different forms of cognition can remain bounded, inspectable, replaceable, and composable.
Our current charter and ethics work centers epistemic integrity, moral precaution, human duty of care, consent and sovereignty, provenance, anti-capture, reversibility, non-extraction, human capability, and responsibility proportional to power. Those commitments are being formalized with their evidence and authority kept explicit rather than backfilled after the fact.
We distinguish working foundations from proposals, and proposals from demonstrated results. A null result is allowed to kill a mechanism. A correction is allowed to propagate. A public standard should remain contestable. Research earns confidence through evidence, reproducibility, and the ability to survive hostile controls, not through how elegantly its parts rhyme with one another.
Featured projects
Explore public projects, protocols and research programs. Each has its own scope and stage of development.
Rosetta is Entif AI's open semantic and provenance protocol for meaning, lineage, uncertainty, interoperability, and governed transformation across changing systems.
IndraNet: a relational fabric for tangible environment interactions, integrating human and digital cognition. Shared physical context, embodied systems and evidence-preserving world modeling.
Bilqis is Entif AI's experimental research program for testing whether explicit semantic structure can reduce the cost of relational and compositional learning.
Open questions. Public work.
