Real bottlenecks eliminated. Real numbers.

Every project starts with a manual problem and ends with an automated solution. Filter by industry to see relevant work.

Retail·OperationsShipped in 3 weeks

Inventory chaos eliminated

Data PipelinePOS IntegrationDashboard
6 hrs → 4 minDaily reporting time
Before

A 120-store retail chain spent 6 analyst-hours every morning manually extracting sales data from 4 disconnected POS systems into a reporting spreadsheet. Errors were routine. Decisions were always a day late.

After

Automated extraction pipeline pulls, validates, and consolidates data from all POS systems into a live dashboard. The morning report now generates in under 4 minutes with zero human intervention.

B2B SaaS·Sales

Lead response rate went from 38% to 100%

+220% pipelineQualified pipeline growth
AI ScoringCRM AutomationLead Routing
Shipped in 5 weeks
The Problem

A mid-market SaaS company was losing 62% of inbound leads because SDRs couldn't respond within the critical 48-hour window. Manual lead scoring meant high-value accounts got buried in the queue.

The Solution

AI-powered lead scoring and automated follow-up sequences now engage every lead within 11 minutes. High-value accounts are flagged and routed to senior reps instantly. Zero new headcount.

Professional Services·Finance

Month-end close cut from 9 days to 2

9 days → 2 daysMonth-end close cycle
ReconciliationFinance AutomationReporting
Shipped in 7 weeks
The Problem

A regional accounting firm's finance team spent 9 business days every month on manual reconciliation across 3 systems. The process required overtime, was error-prone, and pushed advisory work to the back burner.

The Solution

Automated reconciliation pipeline cross-references all three systems in real-time. The finance team now closes in 2 days and has reallocated 70% of that recovered time to client advisory services.

Pharmaceuticals·Regulatory

Regulatory submission prep cut from 6 weeks to 8 days

6 wks → 8 daysIND submission prep
Regulatory AutomationGxP ComplianceData Aggregation
Shipped in 10 weeks
The Problem

A mid-size pharma company's regulatory affairs team manually compiled IND submissions from 12+ source systems. Cross-referencing adverse event data, manufacturing records, and clinical trial results took weeks of painstaking work with constant version control issues.

The Solution

Automated data aggregation pipeline pulls from all source systems into a unified regulatory dossier. Pre-flight checks validate completeness and consistency before submission. The team now focuses on analysis instead of compilation.

Pharmaceuticals·PharmacovigilanceShipped in 12 weeks

Adverse event signal detection moved from months to real-time

NLPPharmacovigilanceSignal Detection
6 months → real-timeSignal detection lag
Before

A global pharma company's safety team relied on manual review of post-market surveillance reports to detect adverse event signals. The lag between signal emergence and detection averaged 4-6 months, creating regulatory risk and delayed response to safety concerns.

After

NLP pipeline continuously processes clinical narratives, social media signals, and spontaneous reports to flag potential adverse events in real-time. Automated triage routes high-severity signals to medical reviewers within hours, not months.

Life Sciences·Research Data

Lab data reconciliation from 8 hours/week to 20 minutes

8 hrs → 20 min/wkData reconciliation time
Data LakeLIMS IntegrationOntology Mapping
Shipped in 9 weeks
The Problem

A research institute's scientists spent 8+ hours per week manually reconciling data across LIMS, electronic lab notebooks, and standalone instruments. Experiment metadata was inconsistent, making reproducibility unreliable at 45%.

The Solution

Unified data lake ingests from all lab systems with automated ontology mapping. Metadata is captured directly from instruments. Experiment reproducibility jumped to 92%, and cross-team data requests shifted from 3-day turnaround to self-service queries.

Life Sciences·Drug Discovery

Molecule screening throughput increased 14×

200 → 2,800/wkCompounds screened
ML PipelineMolecular DockingActive Learning
Shipped in 8 weeks
The Problem

A biotech startup's computational chemistry team ran molecular docking simulations manually - queuing jobs, reviewing results one by one, and re-running failed screens. Throughput was limited to ~200 compounds per week.

The Solution

Automated screening pipeline with ML-driven prioritization screens 2,800+ compounds per week. Active learning model improves hit rates with each iteration. Results feed directly into the team's visualization dashboard.

Drug Discovery·Virtual Screening

Hit identification from 6 months to 3 weeks

6 months → 3 weeksHit identification cycle
Virtual ScreeningML PrioritizationActive Learning
Shipped in 10 weeks
The Problem

A pharmaceutical R&D division screened compound libraries through traditional high-throughput screening - a process that took 6 months and $2M+ per campaign with a hit rate of less than 0.5%.

The Solution

ML-driven virtual screening pipeline processes 10M+ compound library in 48 hours, prioritizing 500 candidates for wet-lab validation. Hit rate improved to 6% (12× traditional HTS). Campaign cost reduced by 80%.

Real Estate·Due DiligenceShipped in 6 weeks

Property due diligence automated from 3 weeks to 2 days

Document AIRisk ScoringAcquisition Pipeline
3 wks → 2 daysDue diligence cycle
Before

A commercial real estate firm's acquisitions team manually reviewed zoning documents, environmental reports, and financial statements for each potential acquisition. Each deal required 3 weeks of analyst time before a go/no-go decision.

After

Automated document ingestion and analysis pipeline extracts key data points from 15+ document types. Risk scoring model flags issues instantly. The team now evaluates 4× more deals with the same headcount.

EdTech·Assessment

Student assessment grading time reduced 92%

5 days → 4 hrsFeedback delivery
NLPAssessment EngineAutomated Grading
Shipped in 6 weeks
The Problem

An online education platform's content team manually graded 3,000+ open-ended student submissions per week. Grading consistency varied by reviewer, and feedback turnaround averaged 5 days.

The Solution

NLP-powered assessment engine provides instant preliminary scoring with 94% agreement rate with human graders. Instructors review edge cases only. Feedback delivery dropped from 5 days to under 4 hours.

EdTech·Adaptive Learning

Course completion rates increased 34% with adaptive pathways

+34% completionCourse completion rate
Adaptive LearningEarly Warning SystemPersonalization
Shipped in 11 weeks
The Problem

A university's online program had a 58% course completion rate. One-size-fits-all curriculum ignored individual learning pace. Student performance data was collected but not acted upon in real time. At-risk students were identified only 2 weeks before failure.

The Solution

Adaptive learning engine adjusts content difficulty and sequence per student in real time. Early warning system identifies at-risk students 6 weeks before failure using engagement and performance signals. Completion rate climbed to 78%.

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