Academic Research & Higher Ed
Accelerate literature reviews, cross-reference peer-reviewed sources, and trace conceptual evolution across decades of academic publishing.
- DOI & citation cross-validation
- Concept lineage mapping
- Export to Zotero, Mendeley, BibTeX
- Plagiarism & bias detection
Corporate Knowledge Management
Transform siloed internal wikis into intelligent, interconnected knowledge bases that grow with your organization.
- Private instance deployment
- Role-based access & versioning
- AI-assisted content drafting
- SSO & LMS integration
Journalism & Media Verification
Verify claims in real-time, access primary source archives, and generate citation-ready backgrounders for complex stories.
- Real-time claim verification API
- Historical context timelines
- Multilingual source translation
- Editorial workflow plugins
Government & Public Policy
Support evidence-based policymaking with traceable data, regulatory cross-references, and demographic impact modeling.
- Regulatory tracking & alerts
- Open-data compliance exports
- Secure sovereign cloud options
- Public accessibility mandates
K-12 & Specialized Education
Age-adaptive learning paths, interactive concept maps, and teacher dashboards aligned with global educational standards.
- Common Core & IB alignment
- Accessibility-first UI (WCAG 2.1)
- Progress tracking & analytics
- Offline-first mobile access
Independent Research & Lifelong Learning
Personalized knowledge graphs, offline reading modes, and seamless note-syncing across your devices.
- Custom topic wikis
- Export to Markdown/Notion/Obsidian
- AI study companion
- Ad-free open access
Built to Integrate
Aevum's knowledge infrastructure is designed to plug into your existing workflows. Whether you're building a research dashboard, training platform, or content management system, our APIs deliver structured, verified data at scale.
import aevum_api from 'aevum-sdk'
async def fetch_verified_context(topic):
client = aevum_api.Client(
api_key="ae_live_xxxx",
version="v2"
)
response = await client.search(
query=topic,
depth="deep",
verify=True,
fields=["summary", "sources", "graph_nodes"]
)
return response.json()
# Output: Structured, citation-ready, bias-scored knowledge