DataWise | AI Decision Systems for High-Stakes Environments

The Problem

Manual processes don't scale. Guesswork doesn't survive audits.

If your team is watching video, reading documents, or scoring compliance by hand — you're spending too much, moving too slowly, and exposing yourself to inconsistency.

Expensive human review

Trained specialists spending hours on tasks that follow repeatable rules. The cost compounds. The throughput doesn't.

Inconsistent decisions

Two reviewers, same inputs, different conclusions. When decisions aren't traceable, they aren't defensible.

No audit trail

In regulated environments, "we checked it" isn't enough. You need structured logs, confidence scores, and reproducible outputs.

What We Build

Systems, pipelines, and platforms. End to end.

From data infrastructure through production AI through the application your team actually uses — we build the full stack. No handoffs. No gaps.

Automated Inspection Systems

Computer vision pipelines that analyze video and images to detect conditions, verify compliance, and replace manual review. Built for regulated environments where accuracy and traceability are non-negotiable.

Compliance-Grade AI Engines

Systems that apply structured rules to unstructured data — turning video, audio, and document inputs into scored, traceable decisions. Every output is defensible. Every step is logged.

Multimodal Data Pipelines

Automated ingestion, transformation, and scoring across video, audio, images, and text. Pipelines that convert raw inputs into structured, decision-ready data — and improve as your data grows.

Custom ML Model Development

Custom model training, fine-tuning, and deployment — not off-the-shelf APIs. Models built on your data, validated against your success criteria, and deployed with monitoring and versioning baked in.

Data Engineering & Infrastructure

Database architecture, ETL pipelines, and data warehousing designed for reliability at scale. Automated ingestion, transformation, and delivery — so your data is always where it needs to be, in the format it needs to be in.

Full-Stack Platforms & APIs

Production web applications, REST APIs, authentication systems, and cloud deployment. Complete platforms where your team interacts with data and AI — purpose-built to your workflow, not a reskinned template.

Decision-Support Tools

Applications where domain experts interact with AI-generated insights to make faster, better-informed calls. Confidence scores, structured outputs, and approval workflows — built for the people making the decisions.

Training & Technical Consulting

Data literacy, statistical methods, and research design — taught by someone who taught it at the university level for years. Team upskilling, methodology audits, and hands-on guidance to build internal capability.

Demonstrated Capability

Built and shipped: a multimodal inspection automation system

A compliance-driven inspection process required trained specialists to manually review hours of video footage, score conditions against regulatory standards, and produce audit-ready documentation. The process was slow, expensive, and inconsistent between reviewers.

We designed and built the full replacement system — from data ingestion through final output — handling the entire pipeline as a solo engineer.

✓ Computer vision pipeline for object and condition detection across video frames
✓ Speech-to-text processing integrated with visual analysis
✓ Structured rule engine mapping detections to regulatory compliance criteria
✓ Confidence scoring and traceable decision chains on every finding
✓ Full-stack review application for domain experts to validate and export results
✓ Complete audit trail — every input, transformation, and output is logged

80%

Less manual review time

5×

Faster report generation

100%

Audit-trail coverage

Engineer. Full stack.

Why DataWise

Engineered differently

Most firms sell code or dashboards. We sell decision systems — built with the rigor of peer-reviewed research and the pragmatism of production engineering.

PhD-level experimental rigor

Every system starts the way a controlled experiment does: defined inputs, measurable outcomes, reproducible results. A decade of published research in cognitive science built that discipline. It shows in the engineering.

Built for messy, real-world data

A decade of working with messy developmental data — noisy signals, missing values, inconsistent formats — means nothing about your data will surprise us. We specialize in multimodal inputs where clean data is the exception, not the rule.

Designed for auditability

In regulated environments, a black box isn't acceptable. Our systems produce traceable decision chains, confidence scores, and structured logs. Every output is defensible. Every process is documented.

Not template-based

No reskinned SaaS. No boilerplate. Every system is purpose-built to your domain, your data, and your compliance requirements. You don't inherit tech debt — you get infrastructure that fits.

About

Bret Eschman, Ph.D.

Founder & Principal Engineer

Ph.D. in Experimental Psychology from the University of Tennessee. Published research in Psychological Science and Developmental Psychology — spanning visual perception, attention systems, and eye-tracking methodology.

A decade of designing controlled experiments, analyzing multimodal datasets, and publishing peer-reviewed research. Then a full transition into software engineering — bringing that same discipline to production systems that process real-world data at scale.

That combination is what makes DataWise different: the scientific rigor to know what to measure, and the engineering capability to build systems that measure it reliably.

We replace manual processes with decision systems.