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AI Proof of Concept Engagements

Before you invest in full AI implementation, validate your use case. BetterWorld Technology designs structured AI proof of concept engagements that test AI solutions against your real data, your real workflows, and your real business outcomes — in 4 to 6 weeks.

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What We Validate

Common AI POC Use Cases

Every POC is scoped around a specific, measurable business problem. We define success criteria upfront so you know exactly what you are evaluating.

Document Processing & Extraction

Automate extraction of structured data from contracts, invoices, reports, and forms using AI. Measure accuracy, speed, and cost reduction against your current manual process.

Intelligent Search & Knowledge Management

Deploy AI-powered search across your internal documents, SharePoint, and knowledge bases. Validate relevance, accuracy, and user adoption before full rollout.

Customer & Ticket Classification

Apply AI classification to support tickets, emails, or customer inquiries. Measure routing accuracy, response time reduction, and agent efficiency gains.

Predictive Analytics

Build and validate a predictive model on your historical data — churn prediction, demand forecasting, anomaly detection, or maintenance scheduling.

Generative AI Copilot

Deploy a controlled generative AI assistant scoped to your internal data. Validate output quality, hallucination rates, and productivity impact on a defined user group.

Process Automation

Identify a high-volume, rules-based workflow and validate AI automation against throughput, error rate, and cost metrics.

Our Process

How We Work

1

Use Case Selection

We work with your team to identify and prioritize AI use cases by business impact, data availability, and implementation feasibility.

2

Data Assessment

We evaluate your data sources for quality, volume, and accessibility. We identify gaps and define what is needed for a valid test.

3

POC Build & Test

We build the POC environment, configure the AI model, and run it against your real data for 2 to 4 weeks with defined success metrics.

4

Results & Recommendation

We present results against success criteria and provide a go/no-go recommendation with a full implementation roadmap if validated.

Common Questions

Frequently Asked Questions

An AI proof of concept (PoC) is a time-bounded, low-risk project that tests whether a specific AI use case delivers real value in your environment before committing to a full deployment. We scope, build, and evaluate the PoC in 4 to 8 weeks, producing clear go/no-go criteria and a decision brief.
We work with Microsoft Azure OpenAI, Microsoft Copilot for M365, GPT-4 via API, custom RAG (retrieval-augmented generation) pipelines, and workflow automation tools like Power Automate and n8n. We choose the stack based on your data environment, security requirements, and the specific use case — not on vendor preference.
Data governance is built into every AI engagement. We evaluate whether your data stays within your tenant (preferred), gets processed by a third-party API, or requires anonymization. For regulated industries — healthcare, financial services, legal — we design for HIPAA and SOC 2 alignment from the start.
The best PoC candidates are high-volume, repetitive tasks with clear inputs and outputs — document summarization, contract review, IT ticket triage, sales email drafting, or data extraction from unstructured documents. We help you identify the highest-ROI use cases before writing a single line of code.

Validate Before You Invest

Start with a use case workshop. We will identify the right POC for your organization and scope it in one session.

|
Newsweek
Most Reliable 2026
|
CRN
MSP 500 2026
|
SOC 2
Type 2 Accredited
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Real Leaders
Top Impact 2025
|
B Corp
Since 2014
|
Newsweek
Most Reliable 2026
|
CRN
MSP 500 2026
|
SOC 2
Type 2 Accredited
|
Real Leaders
Top Impact 2025
|
B Corp
Since 2014