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service
Data quality: Editorially Reviewed
Software development
Language (LLM / NLP)
Agent & prompt engineering
Custom model development
AI strategy & roadmap consulting
Real estate
Staff augmentation
Implementation & integration
Mid-market
Code review & testing
Predictive / classical ML
Healthcare & life sciences
Computer vision
ML lifecycle & data
Capital markets & fintech
Startups
Automotive
Staff augmentation (per FTE)
Retail & e-commerce
Agentic / autonomous
Enterprise
Customer support automation
Time & materials

Vention

Staff augmentation

Offered by Vention Solutions Inc.

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Overview

Vention Solutions Inc. is headquartered in New York and offers AI software development and consulting, machine learning and NLP, computer vision, custom AI agents and chatbots. A proprietary five-stage maturity model guides its AI-enabled software development lifecycle transformation. Engagement options include AI-enabled teams, staff augmentation, dedicated teams and project outsourcing. Industries named are fintech, proptech, adtech, foodtech, healthtech, edtech, automotive and ecommerce. It lists offices serving the US, UK and DACH region.

Pricing model
On request
Regions served
North America, Europe
Categories
Software development, Language (LLM / NLP), Agent & prompt engineering, Custom model development, AI strategy & roadmap consulting, Real estate, Staff augmentation, Implementation & integration, Mid-market, Code review & testing, Predictive / classical ML, Healthcare & life sciences, Computer vision, ML lifecycle & data, Capital markets & fintech, Startups, Automotive, Staff augmentation (per FTE), Retail & e-commerce, Agentic / autonomous, Enterprise, Customer support automation, Time & materials
Last updated
7 October 2026
Published
7 October 2026

Use cases

Software development
Code review & testing
Customer support automation
ML lifecycle & data

Data sources & provenance

Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.

Data quality
Data quality: Editorially Reviewed
Primary source
ventionteams.com
Sources cited
2
Last reviewed
6 October 2026
Last updated
7 October 2026

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