# Multevaluate

*/Occupations/Engineering_and_Architecture_Teachers,_Postsecondary/Problems/ABET_Accreditation_Data_Collection/Startups/Multevaluate*

## Startup Overview

This platform ingests unstructured student coursework and maps it directly to ABET accreditation criteria for engineering and architecture departments. Assessment coordinators and faculty currently spend hundreds of hours manually gathering high, average, and low performance samples across disparate files. Instead of forcing professors to double-grade assignments to satisfy compliance metrics, the software extracts question-level data directly from existing grading workflows.

The system deploys vision-language models to autonomously parse domain-specific artifacts, ranging from handwritten thermodynamics exams to structural analysis code and CAD drawings. It identifies specific proficiencies within individual assignment components and correlates them to mandated institutional learning outcomes. The platform redacts student identifiers and automatically compiles the extracted evidence into audit-ready compliance archives.

Legacy assessment suites like Watermark Taskstream and AEFIS require departments to standardize their rubrics and rely on manual data entry to isolate metrics. By remaining natively format-agnostic and executing autonomous parsing, this software adapts to diverse academic formats without demanding institutional conformity. Faculty retain complete control over their course structures while the platform handles continuous, multi-year outcome tracking in the background.

## Startup Founding Hypothesis

**Problem**: [ABET Accreditation Data Collection](/Occupations/Engineering_and_Architecture_Teachers,_Postsecondary/Problems/ABET_Accreditation_Data_Collection)
**Approach**: a software that ingests multimodal assignment files to map question-level proficiencies
**Competitors**:
- [Watermark Taskstream](/Competitors/Watermark_Taskstream)
- [AEFIS](/Competitors/AEFIS)
- [manual double-grading](/Competitors/manual_double-grading)
**Differentiator2x2**: format-agnostic and capable of autonomous parsing across all artifact types

## Startup Solution Coordinate

**Solution**: [Artifact Matrix](/Software/Artifact_Matrix)

## Startup Offer

**Proof**:
- Engineering departments: aim to eliminate 90% of double-grading hours spent on ABET compliance.
- Assessment coordinators: target compiling multi-year accreditation artifact dossiers in under a week.
- Architecture faculties: intend to map unstructured CAD and physical submissions to rubric proficiencies with zero manual data entry.
**Tiers**:
- Name: Program Pilot · Price: ~$8k–$12k/yr · Inclusions: Mapping for up to 5 courses, designed integration for Canvas or Blackboard API ingestion, automated high/average/low artifact sampling, and PDF/code parsing for up to 1,500 students.
- Name: Department Core · Price: ~$18k–$25k/yr · Inclusions: Unlimited courses for one engineering or architecture department, multi-year outcome tracking, automated PII redaction, and autonomous CAD/Jupyter parsing.
- Name: College Portfolio · Price: ~$28k–$34k/yr · Inclusions: Deployment across up to 4 college departments, cross-curriculum ABET alignment dashboard, and historical assessment data migration capabilities.
**Guarantee**: If the software fails to autonomously extract and map the required high, average, and low student artifacts to your specified ABET criteria within 72 hours of grading completion, we refund the semester's licensing fee.
**Business Function**: ProvideService
**Objection Handlers**:
- Our faculty use distinct, non-standardized rubrics. -> Multevaluate uses multimodal models to parse any native grading format or handwritten exam without forcing department-wide standardization.
- Student data must remain strictly anonymized for accreditation reviewers. -> The platform automatically redacts personally identifiable information from visual and text artifacts before exporting the compliance samples.
- Getting professors to adopt a new assessment tool is impossible. -> Faculty maintain their existing grading workflows; the software connects to the LMS and maps the ABET proficiencies entirely in the background.
- Engineering artifacts like Jupyter notebooks and CAD files break traditional extraction tools. -> The system is specifically built with vision-language models designed to natively read and evaluate unstructured, domain-specific technical files.
**Pricing Architecture**: Tiered
**Agent Checkout Support**:
- agentic-commerce-protocol

## Startup Brand

**Voice**: Academic and authoritative, defined by uncompromising structural precision
**Tagline**: Parse unstructured student artifacts into continuous ABET accreditation evidence
**Icon Concept**: blueprint
**Palette Intent**: institutional-cool
**Visual Identity**: Deep slate and institutional navy support rigid, grid-based typography accented by geometric motifs drawn from architectural schematics.
**Archetype Reference**: the-sage

## Startup Proof Points

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**Pilot Goals**:
- A single-semester pilot covering three core engineering courses, aiming to successfully ingest and map 1,000+ mixed-format artifacts (handwritten PDFs, Jupyter notebooks) to ABET indicators without altering faculty grading workflows.
- A 30-day retrospective data run on the previous semester's assignments, designed to prove the ingestion engine accurately extracts, redact student PII, and categorizes the mandated high, average, and low student samples natively from the LMS.
**Target Metrics**:
- target: 40% reduction in pre-visit faculty administrative hours
- target: 90% autonomous mapping rate of unstructured artifacts to ABET criteria
- aim: 100% automated PII redaction across high, average, and low artifact samples
- target: 0 standardized rubrics forced upon native faculty grading workflows
**Target Case Studies**:
- A large public research university engineering department (Department Chair): eliminate manual double-grading and email-chasing by autonomously mapping unstructured thermodynamics exams and CAD files to specific ABET outcomes.
- A mid-sized private polytechnic institute (Assessment Coordinator): replace manual PII redaction and spreadsheet collation of high, average, and low student samples with a continuous extraction pipeline from Canvas and GitHub.
- A state college School of Architecture (Accreditation Director): shift from episodic, pre-visit data entry scrambles to continuous, multi-year compliance tracking across complex visual artifacts without forcing standardized rubrics.
**Testimonial Targets**:
- Engineering Faculty Member: relief that they maintain their native grading workflow and syllabus structure without double-grading assignments to isolate ABET proficiencies.
- Department Chair: confidence that the continuous, audit-ready matrix of high, average, and low performance samples populates automatically without chasing professors via email.
- Assessment Coordinator: satisfaction that handwritten exam PDFs and complex CAD drawings are parsed and aligned to specific criteria without manual spreadsheet extraction.

## Startup Solution Stack

- [Continuous Attainment Service](/Services/Continuous_Attainment_Service) — Service-as-Software
- [Artifact Parsing Agent](/Agents/Artifact_Parsing_Agent) — Agent
- [Submission Redaction Worker](/Agents/Submission_Redaction_Worker) — Agent
- [Multimodal Evaluation Engine](/Software/Multimodal_Evaluation_Engine) — Software
- [LMS Extraction API](/Software/LMS_Extraction_API) — Software

## Startup Story Brand

**Hero**:
- **Need**: to serve as a strategic evaluator of program quality instead of an administrative nag
- **Want**: to gather evidence of student learning without chasing faculty for high-average-low samples
- **Identity**: the assessment coordinator at an ABET-accredited engineering or architecture department
**Plan**:
- Step: Upload Work · Detail: Submit student artifacts directly from Canvas, Blackboard, or local directories in their native formats.
- Step: Audit Outcomes · Detail: Review the autonomous mapping of question-level data to specific ABET learning outcomes for accuracy.
- Step: Generate Reports · Detail: Export high, average, and low performance samples alongside multi-year continuous improvement dashboards.
**Guide**:
- **Empathy**: You shouldn't still be redacting student PDFs by hand. Watermark Taskstream wasn't built to parse unstructured CAD drawings or local code repositories.
**Problem**:
- **Villain**: manual outcome extraction
- **External**: Assessment data remains trapped in handwritten thermodynamics exams, GitHub repositories, and Canvas rubrics, requiring weeks of manual data entry to satisfy ABET criteria.
- **Internal**: You feel like a bureaucratic paper-pusher rather than an academic leader ensuring program excellence.
- **Philosophical**: Every engineering professor deserves total academic freedom — not the burden of double-grading to satisfy compliance metrics.
**Success**: Your ABET self-study is backed by granular, multi-year evidence extracted automatically from real student work. Faculty maintain their native workflows while you hold a complete, anonymized evidence portfolio.
**One Liner**: Every semester, engineering faculty struggle with double-grading coursework for accreditation. Multevaluate parses unstructured exams and repositories so departments generate ABET-ready evidence automatically.
**Positioning**:
- **So That**: map unstructured artifacts to learning outcomes without forcing standardized rubrics
- **Unlike**: manual question-level LMS extraction
- **For Whom**: ABET assessment coordinators and engineering department chairs
- **Category**: Autonomous accreditation mapping for engineering departments
**Call To Action**:
- **Direct**: Purchase Program License
- **Transitional**: View sample ABET report
**Failure Stakes**:
- Lost accreditation due to insufficient multi-year outcome data
- Wasted faculty labor hours on redundant administrative tasks
- Incomplete evidence for the 2024-2025 cycle site visit
**Transformation**:
- **To**: one of the few coordinators who leads evidence-based program improvement
- **From**: an administrator chasing faculty for spreadsheet outcome mapping
**Controlling Idea**: ABET compliance should be a byproduct of grading, not a separate administrative burden.

## Neighborhood

### What it offers

- [Safety Matrix Engine](/Software/Safety_Matrix_Engine) — offers · Software
- [Outcome Matrix](/Software/Outcome_Matrix) — offers · Software
- [Artifact Matrix](/Software/Artifact_Matrix) — offers · Software

### Competitors

- [Arize Phoenix](/Competitors/Arize_Phoenix) — competes with · Competitors
- [Scale AI](/Competitors/Scale_AI) — competes with · Competitors
- [Arthur AI](/Competitors/Arthur_AI) — competes with · Competitors
- [LangSmith](/Competitors/LangSmith) — competes with · Competitors
- [Patronus AI](/Competitors/Patronus_AI) — competes with · Competitors
- [Human QA Teams](/Competitors/Human_QA_Teams) — competes with · Competitors
- [Watermark Taskstream](/Competitors/Watermark_Taskstream) — competes with · Competitors
- [AEFIS](/Competitors/AEFIS) — competes with · Competitors
- [manual double-grading](/Competitors/manual_double-grading) — competes with · Competitors
- [manual LMS extraction](/Competitors/manual_LMS_extraction) — competes with · Competitors
- [Anthology Portfolio](/Competitors/Anthology_Portfolio) — competes with · Competitors
- [Canvas LMS](/Competitors/Canvas_LMS) — competes with · Competitors
- [AEFIS Assessment Software](/Competitors/AEFIS_Assessment_Software) — competes with · Competitors
- [Manual Spreadsheet Mapping](/Competitors/Manual_Spreadsheet_Mapping) — competes with · Competitors
- [double-grading assignments](/Competitors/double-grading_assignments) — competes with · Competitors
- [double-grading coursework](/Competitors/double-grading_coursework) — competes with · Competitors
- [Canvas LMS rubrics](/Competitors/Canvas_LMS_rubrics) — competes with · Competitors
- [spreadsheet outcome mapping](/Competitors/spreadsheet_outcome_mapping) — competes with · Competitors
- [manual spreadsheet extraction](/Competitors/manual_spreadsheet_extraction) — competes with · Competitors
- [manual question-level LMS extraction](/Competitors/manual_question-level_LMS_extraction) — competes with · Competitors
- [AEFIS Software](/Competitors/AEFIS_Software) — competes with · Competitors
- [manual spreadsheet outcome mapping](/Competitors/manual_spreadsheet_outcome_mapping) — competes with · Competitors

### Embodies

- [Software](/Theses/Software) — embodies · Theses

### Composed of

- [Artifact Parsing Agent](/Agents/Artifact_Parsing_Agent) — composes · Agents
- [LMS Extraction API](/Software/LMS_Extraction_API) — composes · Software
- [Multimodal Evaluation Engine](/Software/Multimodal_Evaluation_Engine) — composes · Software
- [Submission Redaction Worker](/Agents/Submission_Redaction_Worker) — composes · Agents
- [Continuous Attainment Service](/Services/Continuous_Attainment_Service) — composes · Services
- [Accreditation Dossier Service](/Services/Accreditation_Dossier_Service) — composes · Services
- [Artifact Extraction Agent](/Agents/Artifact_Extraction_Agent) — composes · Agents
- [Outcome Alignment Worker](/Agents/Outcome_Alignment_Worker) — composes · Agents
- [Student Redaction Agent](/Agents/Student_Redaction_Agent) — composes · Agents
- [Multimodal Parsing Engine](/Software/Multimodal_Parsing_Engine) — composes · Software
- [LMS Ingestion API](/Software/LMS_Ingestion_API) — composes · Software

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