Company profile

Docere

Persistent-Memory AI for Personalized Education

Industry
Software Development
Employees
6

Docere company summary

Docere is a company in the Software Development industry. On LinkedIn the company has around 6 employees.

What technology does Docere use?

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About Docere

Docere is a memory layer for education — persistent, context-aware, and deeply integrated with your LMS We connect to Moodle or Canvas via LTI 1.3, ingest the full course graph — materials, assignments, submissions, rosters — and construct a live semantic index that both sides of the classroom query against. At the core is a hierarchical memory architecture. Every interaction, concept encounter, and performance signal is captured as a node in a persistent memory tree — a graph that maps relationships between concepts, confusion patterns, and mastery trajectories. Nodes are weighted by recency, relevance, and outcome linkage. The tree grows per-student but aggregates at the course level. Students interact through natural language. Behind every conversation, the system assembles context from their personal memory profile — past struggles, concept mastery state, learning patterns — alongside course content pulled from the LMS. The student just talks. The system already knows what they're working on, what they've been confused about, and what their instructor assigned. For instructors, the memory tree surfaces as a live map of their classroom's cognition — not dashboards of averages, but a structured graph of what each student knows, where they're stuck, and what's connected to what. Zero configuration. One LTI launch. Every piece of course data automatically ingested, embedded, and woven into the graph. Serving 500+ students! We're hiring — if you want to build the infrastructure layer under the next generation of education, reach out :)

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Frequently asked questions about Docere

What does Docere do?

Docere is a memory layer for education — persistent, context-aware, and deeply integrated with your LMS We connect to Moodle or Canvas via LTI 1.3, ingest the full course graph — materials, assignments, submissions, rosters — and construct a live semantic index that both sides of the classroom query against. At the core is a hierarchical memory architecture. Every interaction, concept encounter, and performance signal is captured as a node in a persistent memory tree — a graph that maps relationships between concepts, confusion patterns, and mastery trajectories. Nodes are weighted by recency, relevance, and outcome linkage. The tree grows per-student but aggregates at the course level. Students interact through natural language. Behind every conversation, the system assembles context from their personal memory profile — past struggles, concept mastery state, learning patterns — alongside course content pulled from the LMS. The student just talks. The system already knows what they're working on, what they've been confused about, and what their instructor assigned. For instructors, the memory tree surfaces as a live map of their classroom's cognition — not dashboards of averages, but a structured graph of what each student knows, where they're stuck, and what's connected to what. Zero configuration. One LTI launch. Every piece of course data automatically ingested, embedded, and woven into the graph. Serving 500+ students! We're hiring — if you want to build the infrastructure layer under the next generation of education, reach out :)

How many employees does Docere have?

Docere has around 6 employees on LinkedIn.

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