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Frequently Asked Questions

  • What types of expertise can you offer?
    We focus on providing expertise in the following six areas: - software engineering (primarity backend engineering) - machine learning and data science (recommendation engines, classification systems TensorFlow, Keras, SciKit, Spark etc.) - cloud computing and devops (CICD pipelines, AWS, Docker, Kubernetes etc.)- blockchain (building, deploying and cutomizing blockchain networks and technologies e.g. Hyperledger, Quorum, Tendermint, Cosmos, Plasma, Bitcoin etc. as well as building APIs and integrations with other systems) - product management and business development (building out roadmaps based on customer business use cases for the engineering team, working with business development and sales to explain technical concepts to prospects and clients) - enterprise systems (integrations, refactoring and updates to complex monolithic, often legacy enterprise systems)
  • Where are you based?
    We are based in New York City. Please contact us if you would like to have an initial conversation.
  • If decide to use Hexagon Technologies LLC for a project and later change my mind, can I cancel?"
    Yes. We bill hourly and you can cancel your project at any time if you change your mind. You will only be billed for the work completed up to the point of cancellation and will not be billed for the entire project.
  • How much do your services cost?
    We bill hourly to provide scale up & scale down flexibility to our clients. We are priced competitively with the market. The specific price depends on the nature and complexity of your technology requirements. For more information please contact us to book an initial consultation via phone/zoom so we can understand your requirements and provide you with a detailed quote.
  • Why should I use you instead of hiring full time people in house?
    Some reasons people choose to use us instead of hiring in house are: - "snap on snap off relationship" - you can flexibly scale up or scale down the size of our engagement more quickly and easily than you can using in house engineers - accelarated onboarding and ramp up time - once we have discussed your project we can get to work immediately with no ramp up time - staff augmentation - can rapidly increase your team size when there are tight deliverable deadlines - if you have deliverables needed before next round of fundraising/next press release/next client meetings - our team can make sure you have the technologies delivered when you need them - cheaper than hiring in house - hiring a full time entry level software engineer in a major metropolitan area incurs a significant cost for early stage startups and hiring the wrong person in an early stage team can be fatal. We can deliver the software you require on tight timelines at a cheaper and lower risk price point that in house hiring - additional expertise (for example machine learning, data or cloud) to supplement your in house team's skillset - to bring in subject matter expertise to fulfill a temporary need - to accelerate execution while you carefully choose your next in house hires
  • Do you offer frontend web development?
    Yes. We have a team of frontend developers and UX/UI designers to provider services that may be used as part of your project. We can also provide backend development, data management, cloud infrastructure setup and management, devops and deploying CI/CD pipelines. If you are interested in these services you can contact us to discuss.
  • Have you worked with Ethereum/AWS/Java/Golang/other technologies?
    We have experience with a wide range of technogies and toolsets. Please contact us to schedule an initial consultation to discuss your specific needs.
  • What other projects have you worked on?
    The following is a list of some projects our team has experience in: - building an Ethereum compatible blockchain protocol in Golang - building Bitcoin data analytics tools for cryptocurrency traders - backend engineering on C++ enterprise trade order management system - implementation of recommendation engines - building machine learning classification systems - deploying cloud native microservices architectures using Kubernetes and Docker onto AWS for advertising technology applications - implementing a security library for a payments system - data cleansing, preparation and processing scripts in Python
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