Even if a mall built a website and sold things on a website, it did not make the mall a real internet company. Internet companies can also deliver a new product every week and learn so much faster than a mall, whose design may only be updated once a quarter. Internet companies have clear job descriptions for roles such as product managers and software developers, and these jobs have unique workflows and processes for collaboration. The key here is TALENT and SPEED.
AI, one of the fastest-growing areas of engineering, shows parallels to the rise of the Internet.
In the future, higher economies of scale are likely to occur as machine learning and automation improve and SPEED is the biggest differentiator as founders want to develop more features faster to create a unique competitive advantage. However we all know that finding the right talent is a big challenge, companies have a hard time to solve.
Reliable companies developing custom software have experience in working with disruptive technologies in a variety of industries, however, not all of them understand the importance of getting the right number of skilled talent and most importantly the speed of getting those professionals.
In the era of AI, many companies will once again be keen to outsource their AI team that can help the entire organization move faster.
For example, a senior AI outsourcing vendor can recommend a technology stack to a CTO that helps them drive innovation without compromising their business and technical metrics, or can drastically change the way the CTO manages the infrastructure by showing an example of the successful projects delivered. They help you to avoid additional costs, long delivery times, technical debts, skills shortages and a high defect density, which are always associated with the transition to new unknown technologies.
Every day, Chief Technology Officers face a number of technological, management and strategic challenges. These challenges continue to evolve every day, bringing with them new opportunities and risks. Engineering managers today need to develop robust and resilient strategies that withstand the disruptive trends and lack of talent.
Develandoo is considered one of the key partners for AI companies in this case, with more than 7 years of experience delivering high-profile data-related projects.
The AI team functions are managed by the award-winning lead data scientist – Ara Ghazaryan, the founder of Scylla. Ara has a Ph.D. in optical physics and computer vision and has worked in the world’s leading universities such as the Technical University of Munich, Pusan National University and National Taiwan University.
Another key team member experienced in delivering complex financial AI models is Armen Ghambaryan – an experienced tech leader, AI lecturer, and technical coach, he helps financial companies to assert themselves in an environment characterized by rapid change.
Our tech leaders can enhance your technology management, conduct a technology due diligence process to identify risks to your business, improve the deployment strategy and reduce delivery timeline, and ensure compliance with regulatory and industry regulations and best practices. We are proud of our team members with over 15 years of experience delivering technology and workflows to small and large businesses to extend the reach of their product and mission.
Current clients include startups seeking rapid technology growth such as Neon, and mid-sized companies such as Digitain that harvests the benefits of our experience to keep the market leader position.
Develandoo uses machine learning and automated big data processes to accelerate and improve the design and execution cycles. With these approaches, Develandoo wants to improve the profitability of its customers in sectors that rely on automation as a means of production, for example in the supply chain, automotive, security, and energy sectors.
Data Science and AI team employ about 40 percent of the workforce in Develandoo, with over 20% female scientists, diversity is in our DNA.
While Develandoo scales up the number of customers, data science and automation engineering teams could theoretically grow more slowly as machine learning models and big data infrastructure are reusable across multiple verticals.
If Develandoo increases the number of its projects, probably better economies of scale will be achieved, for our customers as the knowledge we gain could be reused across multiple industries which is impossible in the case of isolated in-house teams.
That said, we will be happy to hear about your project and help you achieve the EFFICIENCY – your founders require in the age of rapid scale and innovation!
Get in touch with me to know more:
- Artificial Intelligence