Mindhive: In pursuit of predictive insight

Current consulting houses are labour intensive, relationship-based and expensive. Outcomes and reporting are latent and not instantaneous, insight is one-directional rather than engaging, shared and collaborative. 

Mindhive is the world’s first crowdsourcing platform enabling you to convene, engage and understand your audience at scale and in real-time.

It’s a scalable crowdsourcing platform built on proprietary technology enabling the disruption of all layers of the consulting industry with instant reporting, natural language processing, AI-driven predictive insights, and maximized global user reach and engagement delivering diverse solutions at reduced costs, increased speed and secured on the blockchain. Mindhive is inexpensive, modern, inclusionary and efficient - so we can quickly get to good ideas and actionable insights.

“Mindhive is a venue for the meeting of minds. It is inexpensive, modern, inclusionary and efficient - so we can quickly get to good ideas and actionable insights” 

Rich Arnold (ex Deputy Managing Director, Bank of America; Executive VP/CFO Charles Schwab & Co; Executive Director, Consolidated Press Holdings Ltd)  

The four questions that we strive to answer:

1. Would the use of AI materially improve the efficiency and accuracy of the matchmaking process between enterprises and experts?

2. Can Mindhive incrementally scale an insightful community over time?

3. Can Mindhive develop novel methodologies for testing predictive insight experiments?

4. What are the most effective workflow processes and/or data capture layers to produce sufficient data, to provide data-driven insight, as a precursor to producing automated intelligence reports, followed by automated AI/ML-driven insight generation?

Mindhive is developing and implementing the following technologies: 

1. High-performance match-making algorithms in order to align clients and users on relevant challenges. The success of the match-making algorithms will rely on accurately mapping high dimensional users to low-dimensional challenges
2. In-depth analytical tools in order to dissect insights created during challenges, gather key data points relating to the ‘DNA’ of insight and then track the key metrics of the insight creation lifecycle
3. Novel machine learning (ML) algorithms in order to convert dialogue into insight based on the challenge generation methodology. In-house natural language processing (NLP) algorithms will be designed for this purpose
4. An SDK (software development kit) to allow for the development of a wider range of challenge generation methodologies. This will allow for a rich methodology ecosystem which gathers insight into which challenge generation methodology is the most robust and versatile
5. Tokenisation of insight combined with blockchain technology to reward, attribute and track unique insights
6. Gamification of the contribution lifecycle, generating more dialogue and in turn making the artificial intelligence (AI)/ML algorithms more robust in its insight generation capabilities, ultimately leading to increased participation.

Join

You can join the Mindhive community for free - grow your network and community, discover new insights and join genuine discussions. Get even more out of Mindhive with Premium access to full functionality to ask unlimited questions and challenges.

Our vision is to be the world’s largest and most technically enabled crowdsourcing consultancy. 

     USER CASE STUDY: Australian Trade and Investment Commission 

“The best ideas come from within an organisation. We recently had over 900 staff participate in our Ideas Challenge – submitting 378 carefully thought-out and argued ideas to improve the way we work.” Dr Stephanie Fahey, Chief Executive Officer, Australian Trade and Investment Commission. Play 2-minute video | CEO ambition | Mindhive Impact