Question 1

What services does Merit Vision provide?

Accepted Answer

We deliver end‑to‑end data solutions: data analytics and BI dashboards, web scraping and data collection, AI/ML model development, and data engineering (pipelines, warehousing, and orchestration).

Question 2

Who is a typical customer?

Accepted Answer

Teams that need reliable data to make decisions—startups, SMBs, and enterprise departments in retail, e‑commerce, finance, and operations. We also support agencies that need a technical data partner.

Question 3

How do we start a project?

Accepted Answer

Send us your use‑case and data sources. We run a short discovery to define goals, success metrics, timeline, and budget, then propose a phased plan (PoC → MVP → production).

Question 4

What does your delivery process look like?

Accepted Answer

We work in short iterations with weekly demos. Typical phases: discovery, solution design, data ingestion, modeling/feature engineering, dashboard or model delivery, and hardening for production.

Question 5

How long do projects take?

Accepted Answer

A focused PoC can take 1–2 weeks, MVPs 3–6 weeks, and production rollouts 6–12+ weeks depending on scope, integrations, compliance, and data quality.

Question 6

Do you hand over documentation?

Accepted Answer

Yes. We provide architecture diagrams, data dictionaries, runbooks, and handover notes. When requested, we add inline code comments and onboarding sessions for your team.

Question 7

How do you price projects?

Accepted Answer

We offer fixed‑price for well‑defined scopes and time‑and‑materials for evolving requirements. We’ll suggest the model that best balances speed, predictability, and flexibility.

Question 8

Can we start with a small pilot?

Accepted Answer

Absolutely. Many clients begin with a fixed‑price PoC to validate approach, then expand into MVP and production once value is proven.

Question 9

How do you handle data privacy and security?

Accepted Answer

We follow least‑privilege access, secrets management, encryption in transit and at rest, and environment isolation. We’re happy to align with your security policies and sign NDAs.

Question 10

Who owns the IP?

Accepted Answer

You do. Upon payment, all work product and deliverables are transferred to you unless we’ve explicitly agreed to use pre‑existing IP or licensed components.

Question 11

Is web scraping legal?

Accepted Answer

We only scrape publicly available data and always honor applicable laws, site terms, and robots.txt. For restricted sources, we obtain prior permission or use official APIs.

Question 12

Can you handle anti‑bot measures and scale?

Accepted Answer

Yes. We use proxy rotation, headless browsers, rate limiting, and resilient pipelines with monitoring and alerts. We design for reliability and respect target systems.

Question 13

What AI/ML work do you do?

Accepted Answer

Forecasting, scoring and recommendations, NLP and extraction, anomaly detection, and custom ML pipelines. We also evaluate and fine‑tune modern LLMs when appropriate.

Question 14

Which tech stack do you use?

Accepted Answer

We are tool‑agnostic. For analytics/ETL: Python, SQL, dbt, Airflow. For ML: scikit‑learn, PyTorch, TensorFlow. For dashboards: your BI of choice. We adapt to your infra and compliance needs.

Question 15

Do you offer ongoing support?

Accepted Answer

Yes. We provide SLAs, monitoring, and maintenance options. Support can include data quality checks, pipeline upkeep, and enhancements as your needs evolve.

Question 16

Where are you based and when are you available?

Accepted Answer

We are based on the Gold Coast, Queensland (AEST). Email responses typically within 2 hours during business hours; proposals within 24 hours.

Frequently Asked Questions

Getting started

Process & delivery

Pricing & engagement

Data & security

Web scraping

AI/ML solutions

Support

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