Clema

Product Introduction

1. Definition: Clema Higher Ed Co-Pilot is an AI-powered data analytics platform (technical category: NLP-driven SaaS for education research) that enables natural language querying of U.S. federal higher education databases.
2. Core Value Proposition: It eliminates manual data extraction by allowing institutional researchers to instantly access IPEDS, College Scorecard, and EADA datasets via conversational queries—accelerating trend analysis, peer benchmarking, and compliance reporting.

Main Features

1. Natural Language Query Engine

   • How it works: Users input questions in plain English (e.g., “Compare 6-year graduation rates for Midwest public universities”). The AI parses intent using transformer-based NLP models, maps queries to federal database schemas (IPEDS/College Scorecard), and retrieves structured data.
   • Technologies: Combines fine-tuned LLMs (e.g., BERT variants) with federated search APIs to normalize terminology across datasets.

2. Automated Peer Benchmarking

   • How it works: Automatically contextualizes institution-specific metrics (e.g., graduation rates) against user-defined peer groups. Calculates comparative averages, generates visualizations (e.g., bar charts), and cites source variables (e.g., IPEDS GRAD_RATE).
   • Technologies: Dynamic clustering algorithms and statistical comparison engines built on Python/Pandas.

3. Cross-Dataset Export Hub

   • How it works: Exports query results as formatted CSVs/Excel files with embedded metadata (source database, variable codes, retrieval dates). Supports multi-dataset merges (e.g., IPEDS finance + Scorecard earnings) without manual reconciliation.
   • Technologies: Apache Arrow for data interoperability and custom citation generators compliant with federal reporting standards.

Problems Solved

1. Pain Point: Manual data retrieval from siloed federal portals (IPEDS/College Scorecard) requires navigating clunky interfaces, downloading fragmented CSVs, and spending hours reconciling variables—delaying critical insights.
2. Target Audience:
   • Institutional Research (IR) directors managing accreditation reports
   • Higher ed policy analysts tracking enrollment trends
   • University administrators benchmarking Title IX compliance (EADA)
3. Use Cases:
   • Real-time tuition competitiveness analysis during budget cycles
   • Automated generation of Common Data Set (CDS) components
   • Athletic program equity audits using EADA variables

Unique Advantages

1. Differentiation: Unlike general BI tools (Tableau) or raw data portals (IPEDS Data Center), Clema pre-maps 10,000+ federal higher ed variables to natural language, eliminating SQL/data-wrangling needs. Competitors lack cross-dataset NLP querying.
2. Key Innovation: Proprietary “schema-to-speech” technology translates technical database fields (e.g., IPEDS EF2020D.ADJ_ATH) into conversational language, reducing query failure rates by 63% (per disclosed benchmarks).

Frequently Asked Questions (FAQ)

1. How does Clema ensure FERPA compliance with federal education data?
   Clema exclusively uses publicly available aggregate data from IPEDS/College Scorecard—no PII is processed. For internal data integrations, it offers SOC 2-certified encryption and BAAs.

2. Can Clema analyze historical trends in College Scorecard metrics?
   Yes, Clema accesses 10+ years of historical data from federal repositories. Query time-series trends (e.g., “Median debt trends 2015-2023 for Ivy League”) to export trend charts with source citations.

3. How does Clema’s NLP handle complex IR terminology like “IPEDS net price”?
   The AI is trained on higher ed taxonomy (e.g., NCES glossaries), recognizing 500+ institutional research terms. It cross-references context (e.g., “net” + “financial aid”) to map to exact variables (IPEDS SFA2020.NETPRICE).

4. Does Clema support custom peer group comparisons?
   Yes, users define peer groups (e.g., Carnegie Classification, enrollment size) to auto-generate benchmarks. Metrics update dynamically as federal data refreshes.

5. What export formats are available for accreditation reports?
   Export to CSV, Excel, or PNG charts. All outputs include auto-generated citations (e.g., “Source: IPEDS 2023 GRAD_RATE, v.12”) for compliance documentation.