See it working before you invest.

Reduce doubt — prove AI works with your real data

Case Study

POC → SAAS Product

Graph database POC evolved into a fully functioning SAAS product

Legal Tech

GPU Costs Eliminated

POC proved an open-source LLM could run on CPUs — no vendor lock-in, no GPU spend

Delivery

4 Weeks

From hypothesis to go/no-go recommendation

Pricing

Fixed Price

One price, no hourly billing, no surprises

WHAT IS AN AI PROOF OF CONCEPT?

A Proof of Concept is a focused, time-boxed engagement designed to answer one critical question: does this AI approach actually work with your data?

In 4 weeks, we build a testable prototype using your real data (or representative samples), define measurable success criteria, and deliver a clear recommendation on whether to proceed to production.

No guessing. No handwaving. No hourly billing. You pay a fixed price for the entire POC — no matter how many iterations, experiments, or model comparisons it takes. You see the AI working — or you learn exactly why it doesn't — before committing to a full build.

WHAT WE DELIVER

Testable Prototype

A working AI system you can interact with, test, and evaluate against your actual use case requirements.

Test Cases & Metrics

Predefined evaluation criteria with quantitative results so you can objectively assess performance.

Performance Benchmarks

Accuracy, latency, cost-per-request, and other key metrics measured against your success thresholds.

Recommendation Report

Go/no-go recommendation with technical findings, limitations discovered, and suggested improvements.

Production Scope

If validated, a detailed scope document for the production build including architecture, timeline, and team requirements.

Lessons Learned

Key technical insights about your data, model behavior, and integration challenges discovered during the POC.

Have a use case in mind?

Tell us about it and we'll assess whether a POC is the right next step — or if you need something else first.

POC TYPES WE BUILD

Patterns we have validated across dozens of engagements

Advanced RAG

Retrieval-Augmented Generation for querying complex internal documents and data.

Document ingestion pipeline
Semantic search over your data
Cited, traceable answers
Multi-format support (PDF, docs, databases)

Computer Vision

Image and video analysis for quality control, object detection, and visual inspection.

Object detection and classification
Defect and anomaly detection
OCR and document digitization
Real-time video processing

Cognitive Automation

AI-powered workflow automation for repetitive, judgment-intensive tasks.

Document classification and extraction
Decision support systems
Data enrichment and validation
Process orchestration

ETL & Data Pipelines

AI-enhanced data extraction, transformation, and loading for complex data ecosystems.

Intelligent data mapping and matching
Unstructured-to-structured data conversion
Data quality scoring and cleansing
Automated schema detection

Dashboards & BI

AI-powered analytics dashboards that surface insights and answer questions in natural language.

Natural language querying over your data
Automated insight generation
Anomaly and trend detection
Custom KPI tracking and alerting

Advanced ML Models

Custom machine learning models for prediction, classification, and optimization tasks.

Demand forecasting and time series
Churn and risk prediction
Recommendation engines
Optimization and scoring models

Industrial Yield Optimization

AI-driven sensor cross-correlation to identify optimal machine configurations and reduce material waste.

Sensor cross-correlation analysis
Good vs. bad output classification
Real-time monitoring dashboard
Optimal configuration recommendations

SIGNS YOU NEED A POC

You have a use case but doubt it will work

Your team has identified an AI opportunity, but nobody has proven it's technically feasible with your data.

Stakeholders need to see results before approving budget

Decision-makers want tangible evidence — a demo they can touch — before greenlighting production investment.

You need to compare approaches

Should you use LLMs, traditional ML, or rule-based automation? A POC answers this empirically.

Your data quality is uncertain

You suspect your data may have issues. A POC surfaces data quality problems early, before they become expensive.

HOW IT WORKS

A focused 4-week sprint with weekly checkpoints

Week 1

Hypothesis + Data

Define success criteria, gather data samples, and establish the evaluation framework.

Weeks 2-3

Build

Develop the prototype, iterate on model selection and tuning, and conduct internal testing.

Week 4

Validation

Run test cases, measure against success criteria, and deliver go/no-go recommendation.

Ready to prove your AI idea works?

In 4 weeks you'll have a working prototype and a clear go/no-go answer.

FREQUENTLY ASKED QUESTIONS

Do we need to complete Discovery first?

Not necessarily. If you already have a clear use case, defined success criteria, and available data, we can go directly to a POC. We will assess readiness in our initial conversation.

What data do you need from us?

We need representative samples of the data the AI will process. This can be anonymized or synthetic — what matters is that it reflects real-world patterns and edge cases.

What if the POC shows the approach doesn't work?

That is a valid and valuable outcome. You avoid investing in a production build that would fail. Our recommendation report will explain why it did not work and suggest alternative approaches if they exist.

How much does it cost?

Every POC is a fixed-price engagement. You pay one price for the entire 4-week project — no matter how many iterations, model experiments, or pivots it takes. Get in touch and we'll share the exact number based on your use case type.

When is a POC NOT the right choice?

If you do not have a specific use case yet, start with Discovery. If you already have a validated prototype, skip directly to AI Squad for production build.

Talk to an AI Expert

Tell us about your project and we'll get back to you within 24 hours with a tailored recommendation.

Your data is safe with us. We never share your information with third parties.