New webinar on 3rd March 2026 | 9:00 am PT
In this webinar, discover how Sopact Sense revolutionizes data collection and analysis.
Legacy submission tools weren’t built for collaboration or AI. Sopact Sense helps you streamline, score, and scale with confidence.
Legacy submission tools weren't built for collaboration or AI. Here's what that actually costs.
Most teams still review hundreds of applications using manual workflows that fragment data, delay decisions, and frustrate both reviewers and applicants. Applications arrive through one system, documents through another, scores land in spreadsheets, and communication lives in email. By the time a committee meets to decide, staff have spent weeks reconciling fragments instead of comparing candidates.
The cost of this fragmentation is staggering. For a program receiving 200 applications, the typical cycle looks like this: Day 1, forms arrive in scattered formats with no shared identifiers. By Day 3, staff are exporting to Excel and manually entering missing data—40+ hours of cleanup before a single review begins. Reviewer assignments take another 3–5 days of email coordination. By Day 21, someone discovers 15 applications are missing required documents. Six weeks later, the committee meets with printed spreadsheets and no ability to drill into supporting evidence. 80% of the entire cycle is spent managing the process, not evaluating quality.
The AI era hasn't fixed this. Most platforms bolt on generative AI that sounds impressive but collapses when the underlying data is messy. They can't analyze essays and narratives at scale, can't auto-assign reviewers by expertise, and can't connect this year's applications to next year's outcomes. The result: qualitative data—often the most important signal—remains unmeasured, and reviewers default to subjective impressions that are impossible to compare consistently.
Sopact Sense reimagines submission management as a continuous intelligence system, not a data collection tool. Every applicant receives a unique Contact ID at first interaction. Every form, document upload, reviewer score, and follow-up links back to that single record—no exports, no deduplication, no spreadsheet merges. Intelligent Cell extracts comparable themes from narratives. Intelligent Columns auto-route submissions to reviewers by expertise, workload, and conflict-of-interest rules. Intelligent Grid generates decision-ready reports in minutes by answering plain-English questions across all your data.
The result: 40+ hours of data cleanup eliminated entirely. Reviewer assignment compressed from days to minutes. Review cycles cut by 70%—from six weeks to ten days. And decision reports that used to require days of manual preparation now generate on demand. This is the shift from submission administration to submission intelligence.
See how it works in practice:
This isn't about replacing reviewers. It's about eliminating the 80% of work that isn't review — so your team spends time on judgment, not janitorial data tasks.
Submission management software is a platform that automates the complete application lifecycle — from intake and deduplication through scoring, reviewer coordination, and decision reporting — so organizations can evaluate quality instead of managing logistics.
Unlike survey tools (Google Forms, SurveyMonkey) that stop at data collection, or CRMs that track relationships but can't evaluate content, submission management software handles what happens after someone clicks "Submit": routing applications to qualified reviewers, applying consistent scoring criteria at scale, analyzing qualitative narratives alongside quantitative data, and generating decision-ready reports for committees.
The best submission management platforms today are AI-native — meaning artificial intelligence isn't bolted on as a premium add-on, but woven into every step of the workflow. This matters because the highest-value part of any application — the essay, the pitch deck, the project narrative — has historically been the hardest to evaluate consistently at scale.
Submission management software serves any organization that receives more applications than they can manually review with consistency. Common use cases include:
Grantmakers and foundations receiving hundreds of project proposals per funding cycle, needing to match proposals to program officers with relevant expertise, and reporting on funding decisions with evidence.
Scholarship programs at universities and nonprofits managing thousands of student applications across multiple criteria — academic merit, financial need, leadership potential, essay quality — while maintaining equity and consistency across large reviewer panels.
Accelerators and incubators evaluating startup applications, analyzing pitch decks and business plans for market opportunity, team readiness, and product viability, then tracking cohort companies through program milestones to demo day.
Pitch competitions handling sudden surges of applications (often 500 to 5,000+) with tight timelines, needing AI to rapidly filter to the strongest candidates so human judges can focus on the top tier.
Conference organizers collecting session proposals, routing abstracts to peer reviewers, managing conflict-of-interest screening, and analyzing submission themes to build balanced programs.
Compliance teams requiring regulatory submissions or internal approval workflows where document completeness and consistency must be verified before human review.
Most organizations start with tools they already have — Google Forms, SurveyMonkey, even email. Some upgrade to dedicated platforms like Submittable or SurveyMonkey Apply. These tools solve the intake problem, but they leave the three hardest parts of submission management unaddressed.
Applications arrive in one system. Documents get uploaded to a shared drive. Reviewer scores live in spreadsheets. Communication happens over email. By decision day, each application has been touched in four or five different tools, and nobody has a single view of where things stand.
A typical manual workflow looks like this:
Day 1: 200 applications submitted via online form.Day 3: Staff export to Excel, manually enter missing demographic data.Day 7: Email reviewer assignments with file attachments.Day 14: Chase reviewers for scores via email, manually enter into another spreadsheet.Day 21: Realize 15 applications are missing required documents. Start over with those applicants.
Every handoff between tools introduces errors. Every export loses context. Every email creates a version control problem. Organizations report spending 40+ hours per review cycle just reconciling data — before any evaluation happens.
Matching 300 applications to 15 reviewers based on expertise, workload capacity, and conflict of interest is a multi-day spreadsheet exercise. Factor in multiple review stages — initial screening, deep evaluation, finalist selection — and coordination can consume more time than actual review.
Traditional platforms handle reviewer assignment in one of two ways: completely manual (administrator reads each application, looks up reviewer expertise, checks for conflicts, balances workload, sends assignments by email) or semi-automated (basic round-robin distribution that ignores expertise matching). Neither approach scales when you receive 3,000 applications in a week.
The coordination tax also introduces unconscious bias. Reviewers who get assignments first have more time and energy. Those who get a disproportionate share of applications from certain institutions or demographics develop pattern fatigue. Without automated load balancing and blind review capabilities, the process itself skews outcomes.
Grant narratives, scholarship essays, pitch deck summaries, and project proposals contain the richest evaluation signals — innovation potential, leadership capacity, community impact, technical feasibility. But traditional platforms can't analyze text at scale.
The result: two reviewers read the same essay and extract completely different conclusions. One sees "strong leadership potential." Another sees "moderate engagement." Without consistent extraction criteria applied to every submission, committees spend their meetings debating whose subjective impression is correct instead of comparing evidence.
This isn't a small problem. For programs where qualitative factors drive selection — pitch competitions, fellowship programs, research grants — the inability to consistently measure narratives means the most important evaluation dimension is the least reliable.
Sopact Sense approaches submission management as a continuous intelligence system — not a data collection tool with review features bolted on. The platform integrates three capabilities that traditional systems treat as separate problems: clean data capture, automated workflow orchestration, and real-time AI-powered analysis.
Every data quality problem in submission management traces back to a single architectural failure: applicants don't have persistent identities in the system.
When someone submits through a traditional form tool, they're just a row in a spreadsheet. If they submit again to correct a mistake, that's a duplicate. If you collect additional materials later, that's a new disconnected record. If they apply to a different program next year, you start from scratch.
Sopact Sense solves this at the architecture level. Contacts create unique IDs for every applicant — like a lightweight CRM built into the submission platform. Every form submission, document upload, reviewer score, and communication links back to that single identity.
This means: no duplicate applications when someone submits twice, no lost context when you collect follow-up materials, no data reconciliation before review committees can start working, and no "starting from scratch" when the same applicant returns for the next cycle.
Applicants receive unique links to update their existing records — correcting errors, uploading missing documents, or adding supplementary materials — without creating new entries. This alone eliminates the 40+ hours organizations typically spend on data cleanup per review cycle.
This is where Sopact Sense fundamentally differs from every other submission management platform on the market.
The Intelligent Suite — four AI analysis layers working together — transforms how organizations evaluate submissions:
Intelligent Cell analyzes individual submissions at the field level. Upload a one-page company writeup, a grant narrative, a scholarship essay, or a 200-page PDF, and Intelligent Cell extracts structured insights based on your rubric. Leadership indicators, innovation themes, feasibility concerns, compliance gaps — whatever criteria matter to your program, AI applies them consistently to every submission.
Intelligent Row generates complete summaries of each application. Instead of reading 50 applications sequentially, reviewers scan AI-generated profiles that highlight strengths, concerns, and scoring across every criterion. Review 50 applications in the time it takes to read 10.
Intelligent Column compares patterns across all submissions in a dimension. How does the entire applicant pool score on innovation? Where do the strongest candidates cluster geographically? Which rubric criteria produce the widest variance? Column-level analysis reveals patterns invisible in application-by-application review.
Intelligent Grid creates decision-ready reports from the full dataset. Type a question in plain English — "Compare the top 25 applicants across leadership, innovation, and financial viability with supporting quotes from their narratives" — and get a formatted report with charts, evidence, and exportable data in minutes.
The critical differentiator: this analysis runs on natural language prompts, not code. Program staff define scoring criteria, rubric weights, and analysis questions the same way they'd brief a human reviewer. No technical expertise required, no data team dependency, no weeks-long dashboard building process.
Most organizations wait until they have all submissions before building their evaluation process. Sopact Sense flips this approach.
As soon as 10 applications arrive, you can start building reports, testing your scoring rubric, and refining your AI prompts. Found that your rubric weights "innovation" too heavily relative to "feasibility"? Adjust the prompt and re-run analysis on existing submissions — scores update automatically.
This iterative approach means your evaluation process is battle-tested before the bulk of applications arrive. By the time you hit 500 or 3,000 submissions, your rubric, scoring criteria, and report formats are already optimized. You can even run simulations with synthetic data before opening applications to the public.
The result: what used to require weeks of post-deadline manual processing now happens continuously as applications arrive. When submissions close, your committee report is already drafted.
Organizations evaluating submission management software typically consider three categories of solutions: dedicated submission platforms (Submittable), application management add-ons to survey tools (SurveyMonkey Apply), and AI-native platforms (Sopact Sense). Here's how they compare on the dimensions that matter most.
Submittable added "Automated Review" as a premium, custom feature coordinated through their sales team. It applies automated scoring based on custom rubric criteria and can scan essays, images, and video. However, AI is an add-on to the core platform, not native to the architecture. Pricing and availability are negotiated separately.
SurveyMonkey Apply offers basic workflow automation — eligibility screening, stage movement — but no AI-powered content analysis. Reviewer scoring is manual. Qualitative narratives (essays, proposals) cannot be analyzed at scale.
Sopact Sense treats AI as core infrastructure, not a premium feature. The Intelligent Suite (Cell, Row, Column, Grid) is available to every user from day one. Natural language prompts replace technical configuration. Programs can iterate on scoring criteria in real-time as applications arrive.
Submittable handles follow-up forms and can link materials to submissions, but each project creates its own data silo. Cross-program applicant tracking requires manual effort. Duplicate prevention is post-hoc, not architectural.
SurveyMonkey Apply treats each application form as a separate survey. Linking data across stages requires manual configuration. No unique applicant IDs persist across programs or years.
Sopact Sense generates unique Contact IDs at the point of first submission. Every subsequent form, document, score, and communication links to that identity automatically. Programs that run annually can track the same applicant across multiple cycles without any manual reconciliation.
Submittable allows reviewers to score applications using custom rubrics (including qualitative criteria), but the analysis is human-driven. There's no AI extraction of themes from narratives or automated comparison of qualitative signals across applicants.
SurveyMonkey Apply provides no qualitative analysis capabilities. Essays and narratives must be read individually by human reviewers.
Sopact Sense uses Intelligent Cell to extract structured insights from unstructured text — essays, pitch decks, PDFs, interview transcripts — and compares those insights across applicants using Intelligent Column and Grid. Reviewers still make the final judgment, but they start from AI-generated evidence instead of blank impressions.
Submittable reports that over half of customers launch in 14 days. Enterprise features may require longer implementation timelines.
SurveyMonkey Apply offers quick setup for basic application forms, but complex multi-stage workflows with reviewer coordination take longer to configure.
Sopact Sense is designed for same-week deployment. Organizations with tight timelines (such as a pitch competition that needs applications open within days) can have a complete submission workflow — intake, scoring rubric, reviewer assignment, and reporting — operational within 1-2 days with guided onboarding support.
Consider a university entrepreneurship center partnering with a major sports organization to host a high-profile pitch competition. The challenge: open applications to any startup even tangentially related to the organization's industry (apparel, media, technology, health, entertainment), expect 3,000+ submissions based on a comparable previous event, and identify the top 35-50 finalists for celebrity judges — all within a six-week window.
The university's internal system couldn't scale beyond a few hundred applications and had no AI capabilities. They needed a platform that could handle massive volume, apply consistent scoring criteria based on a custom rubric, and filter thousands of submissions to a manageable finalist pool without requiring their small team to read every application manually.
They also needed a second submission stage: once AI and initial reviewers identified the top candidates, those teams would submit 3-5 minute video pitches for human judges. The platform needed to link video submissions back to original applications, maintaining a single applicant record throughout.
Week 1: Build and Test
The team designed their application form — basic company information plus a one-page writeup of the business. Using Sopact Sense's Contacts, every applicant automatically received a unique ID.
Before opening public applications, they ran 10 test submissions through the system. Using Intelligent Cell, they configured AI prompts based on their rubric criteria: market opportunity, team strength, innovation level, relevance to the industry, and pitch-readiness. They refined scoring prompts iteratively until the AI output matched their expectations.
Week 2-4: Collect and Analyze in Real-Time
As applications arrived, Intelligent Cell scored each one-page writeup against the rubric automatically. Intelligent Row generated summary profiles. Program staff monitored incoming scores, adjusted criteria weights after the first 50 submissions, and re-ran analysis — all scores updated automatically.
By the time applications closed at 2,800 submissions, the team already had a ranked list of candidates with AI-generated scores, supporting evidence extracted from writeups, and comparison reports across all rubric dimensions.
Week 4-5: Human Review of Top Tier
Using Intelligent Grid, the team generated a report comparing the top 60 candidates across all criteria. Human reviewers focused their attention on this short list — reading full narratives, evaluating nuances AI couldn't capture (personal story, presentation style, community connection), and selecting 35 teams for the video round.
The 35 finalists received unique links to submit their video pitches. Videos linked automatically to their original application record — no separate system, no data reconciliation.
Week 5-6: Celebrity Judge Review
The judging panel reviewed 35 video pitches with full context: AI-generated summaries, rubric scores, key quotes from narratives, and reviewer notes — all accessible in a single view per applicant.
Timeline: Application open to finalist selection in 4 weeks (vs. 8-12 weeks with traditional manual process).Staff hours: ~30 hours of human review for 2,800 applications (vs. estimated 400+ hours manual).Consistency: Every application scored against identical criteria. No reviewer fatigue bias. No late-stage applications receiving less attention than early ones.Quality: Celebrity judges praised the finalist quality, noting that the selection process surfaced candidates they wouldn't have found through traditional screening.
Foundations and government agencies use Sopact Sense to collect project proposals, route them to program officers and external reviewers with matched expertise, extract key themes from narratives (innovation approach, community engagement, sustainability plans), and generate comparison reports for funding committees. Intelligent Row provides AI-generated summaries of each proposal, letting committees scan 50 applications in the time it takes to read 10.
Educational institutions and nonprofits managing scholarship competitions use Contacts to track applicants across multiple years. Intelligent Cell extracts comparable themes from essays — leadership, resilience, academic commitment — while automated rubrics ensure consistent scoring across reviewer panels. Programs report cutting review cycles by 60% while improving decision confidence through evidence-based comparisons.
Accelerator programs evaluating hundreds of startup applications use Intelligent Cell to analyze pitch decks and business plans, extracting market opportunity signals, team experience indicators, and product readiness levels. Reviewer assignment automation matches applications to mentors with relevant industry expertise. Intelligent Grid generates cohort comparison reports identifying portfolio balance and gaps.
Time-compressed evaluation events — from NFL Draft pitch competitions to university demo days — use Sopact Sense to handle surge volumes (500 to 5,000+ applications) with AI-powered initial screening. The platform's iterative rubric refinement means scoring criteria are optimized before the bulk of applications arrive, and human judges focus exclusively on the top tier.
Academic conferences and industry events collect session proposals, route abstracts to track chairs and peer reviewers, and analyze submission themes to identify emerging topics. Automated conflict-of-interest screening ensures reviewers don't evaluate submissions from colleagues. Centralized communication keeps submitters updated on review status.
Organizations requiring regulatory submissions or internal approvals use Intelligent Cell to scan documents against compliance checklists, automatically flag missing requirements or inconsistencies, and route flagged items to appropriate stakeholders. This transforms review from manual line-by-line processing into an exception-based workflow.
One of the most common concerns organizations have about switching submission management platforms is implementation time. Enterprise tools like Submittable report that most customers launch in 14 days, and some complex deployments take longer.
Sopact Sense is designed for organizations that can't wait weeks. Here's what a typical rapid deployment looks like:
Day 1: Design your application form and define your rubric. Create the intake form using the drag-and-drop builder. Define the scoring criteria that matter to your program. Set up Contacts for unique applicant identification.
Day 1-2: Test with synthetic data. Submit 10 test applications. Configure Intelligent Cell prompts to score against your rubric. Run Intelligent Grid to generate a sample report. Refine until output matches expectations.
Day 2-3: Open applications to the public. Share your application link. As submissions arrive, Intelligent Cell scores them automatically. Monitor quality and adjust rubric weights as needed.
Ongoing: Iterate in real-time. Add subsequent data collection stages (video submissions, interviews, references) as your process advances. All data links back to the original Contact ID. Generate committee reports on demand.
No IT department involvement required. No vendor customization fees. No waiting for implementation consultants. The platform is self-service by design, with unlimited onboarding support calls available.
