Synthesize academic knowledge with scholarly rigor.
Shodh federates searches across peer-reviewed repositories, reads full-text literature, and constructs cited syntheses — eliminating hallucinations so you can focus on deep intellectual work.
Selective state-space architectures like Mamba overcome the quadratic memory bottleneck of multi-head attention through linear-time sequence compression. Empirical evals indicate hybrid SSM-attention layers achieve optimal throughput-to-perplexity trade-offs on 100k+ context benchmarks..
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
"By making SSM parameters functions of the input, our selection mechanism filters out irrelevant tokens while propagating critical state information with O(L) compute."
Five principles that separate scholarship from chatbots
Consumer AI treats research as casual small talk. Shodh treats literature synthesis as rigorous intellectual work — calm, automated, traceable, and verified.
Calm editorial focus, zero conversational fluff
We reject the frantic neon animations, hype, and emojis of consumer chatbots. Shodh provides an archival paper desk engineered for sustained contemplation and hours of deep reading.
"Sure thing! Here is everything you need to know about cellular senescence in aging! Basically cells stop dividing. Some studies say it might cause cancer, or maybe prevent it? It's really fascinating! Let me know if you want me to write a poem about it! ✨🚀"
Senescent cells accumulate a secretory phenotype (SASP) characterized by IL-6 and MMP secretion, driving chronic tissue inflammation while paradoxically inhibiting tumorigenesis in early-stage pre-malignant lesions[1] López-Otín et al., Cell. Targeted clearance via senolytics restores regenerative capacity in murine models[2] Kirkland & Tchkonia, Nat Rev.
Mechanical tasks, not cognitive load
Your intellect is for hypothesis generation and synthesis. Shodh automates Boolean translation, multi-journal querying, and citation formatting.
Query Expansion
AutonomousTranslates natural questions into Boolean logic & MeSH academic search strings.
Multi-Index Retrieval
ParallelSimultaneously queries PubMed Central, arXiv, Semantic Scholar & Europe PMC.
Full-Text Parsing
Deep OCRExtracts methods, results, and sample sizes from open-access academic PDFs.
Citation Verification
100% GroundedCross-checks DOI validity, extracts exact quotes, and formats BibTeX / APA.
Absolute transparency in evidence
Never trust an ungrounded assertion. Every single claim synthesized by Shodh is paired with a direct inline citation linking to authors, year, publication, and primary extracted quote.
While the Transformer architecture revolutionized sequence modeling through pairwise self-attention,its quadratic compute scaling motivated selective state-space alternatives like Mamba.Recent mathematical proofs now unify both frameworks, proving that selective SSMs and linearized attention are structurally dual.
Attention Is All You Need
"The dominant sequence transduction models are based on complex recurrent or convolutional neural networks. We propose the Transformer, a model architecture eschewing recurrence entirely."
Streaming by default
Real-time streaming is intellectual verification. Inspect live query expansion, database lookups, and citation grounding as tokens arrive in real time.
From hypothesis to verified insight in three stages
Academic research traditionally requires hours of tedious Boolean syntax and skimming paywalled PDFs. Shodh unifies retrieval and synthesis into a streamlined workflow.
Formulate Your Inquiry
Enter your research question in ordinary academic English. No specialized Boolean wildcards or complex query operators needed.
"Mechanisms of resistance to 3rd-gen EGFR inhibitors in NSCLC"
Federated Search & Extraction
Shodh queries multiple academic databases simultaneously, extracting methods, cohorts, and results directly from full-text PDFs.
Cited Synthesis & Export
Receive structured summaries with clickable inline citations, DOI links to primary papers, and single-click BibTeX exports.
Osimertinib resistance predominantly occurs via on-target C797S mutations[1]and bypass MET amplification.
Watch Shodh in action
See how Shodh processes complex academic inquiries, queries literature databases in parallel, and delivers cited syntheses in seconds.
Frequently answered questions
Everything you need to know about early access, scholarly source coverage, and citation verification.
What is Shodh and who is it designed for?
Shodh is an AI-powered research assistant engineered specifically for academics, graduate scholars, clinical researchers, and scientific investigators. Unlike consumer chat tools that generate unverified text, Shodh federates queries across peer-reviewed databases (PubMed, arXiv, Semantic Scholar, Europe PMC) and synthesizes literature with verified, inline citations.
Which academic databases and repositories does Shodh search?
Shodh connects simultaneously to open-access preprint servers and scholarly indices, including PubMed Central, arXiv, Semantic Scholar, Europe PMC, and bioRxiv. Our retrieval engine converts plain inquiries into academic search strings, extracts full-text findings from open-access PDFs, and verifies publication DOIs in real time.
How does Shodh eliminate AI hallucinations and ensure citation integrity?
Every synthesized sentence in Shodh is strictly anchored to an extracted paragraph in a retrieved paper. You can click any inline citation badge to view the author, year, journal, DOI link, and the primary excerpt. Claims without direct evidentiary backing are systematically flagged and rejected during synthesis.
Can I upload my own PDFs, Zotero libraries, or custom literature corpora?
Direct PDF ingestion and Zotero / Mendeley library synchronization are currently in active beta testing. Today, Shodh specializes in autonomous federated web & academic repository retrieval. Custom corpus ingestion will be rolled out to all users in the upcoming release.
How is my proprietary research and query data protected?
Your research hypotheses, queries, and workspace notes are never used to train public machine learning models. Session data is encrypted in transit and at rest. We adhere to rigorous academic privacy standards so you can explore novel hypotheses with complete intellectual security.
How do I start using Shodh?
Shodh is freely accessible in public beta at app.shodhai.app. You can sign in with your academic or Google account and immediately begin running multi-journal searches, generating literature syntheses, and exporting structured citations.
Have inquiries about your specific field?
We are working directly with academic researchers to expand journal coverage.
Elevate your inquiries with scholarly clarity
Join researchers, graduate scholars, and clinicians using Shodh to federate literature searches, verify assertions, and synthesize findings in seconds.