Artificial Intelligence, machine learning, and Big Data won’t add much value to your business unless you carefully plan for it. By now, we’ve seen many organisations jump into data (science) head first, and failing to provide immediate value to their business.
All these new technologies promise to fundamentally change businesses, and being late to the game might be fatal. However, no algorithm will magically add value to your company without a clear strategy and value proposition.
With years of experience in data-driven companies, we help you select and specify projects that immediately add value and impress your stakeholders. We help you develop a roadmap that starts with simple solutions as a proof of concept, assist you in taking incremental steps towards a more advanced solution, and finally help you transition into a fully productized solution.
We help you identify opportunities by:
Our process in short:
Data, artificial intelligence, and machine learning are on their way to fundamentally change many industries. They allow services that were previously unthinkable, either technically or economically. Top-of-mind examples are self-driving cars, chat bots, and self-landing rockets.
But these are just the shiny revolutions on the surface. The real revolution is happening right below the surface. Google, Facebook, and Amazon’s ranking algorithms are changing how we interact with content and make decisions. Even classical businesses like delivery now heavily rely on machine predictions to optimize routes, order packaging, and traffic patterns.
Many companies understand the opportunity and are aiming to implement these new technologies. Yet few succeed: 87% of machine learning projects fail to be implemented. A key driver is the technological complexity but even more important is immediate value to the business. Most AI/ML projects fail to deliver any value for the business within a reasonable time frame.
We leverage our expertise from countless AI/ML projects to help you create immediate value for your business by starting with a simple prototype and only moving towards more advanced technologies after value is proven. As in product development, we start with a minimum viable product that shows e.g. that a certain feature is feasible in production. Then we assess together the potential to add value and only then start using cutting edge technologies. This approach helps us focus on value, impact, and speed.
From there on we iterate and help you build world-class technology based on years of industry experience and the newest research papers. Leading academic researchers on our team ensure we’re always on the cutting edge of technology.
What is the common denominator behind big tech companies’ success? They all practice data-driven decision making. Meaning they make decisions based on scientific principles to guard themselves against biases like, e.g. confirmation bias, base-rate fallacy, and more. A data-driven approach ensures high-quality decisions in today’s fast changing world.
How we can help:
Today strong data capabilities are core for many businesses. Start-ups often aspire to embed data in their DNA. Additionally, founders are more aware of the technological possibilities and design of their core product with machine learning capabilities in mind.
We help young and established companies to break down their roadmap and set clear goals for their machine learning and data science functions. From there we define the team that’s required to achieve their goals.
In the hiring process, we support by using our established network to find high-quality candidates, help interviewing, and build robust interviewing process for future hires. This helps companies to avoid false starts by hiring inexperienced or unqualified candidates. After all, data science is a very technical field and it’s often impossible for an outsider to judge the quality of a candidate.
Ask our friends at Orderchamp how we helped them building their world-class data science teams.
@ 2024 acmetric. All rights reserved. | Privacy Policy
Cookie | Duration | Description |
---|---|---|
cookielawinfo-checkbox-analytics | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics". |
cookielawinfo-checkbox-functional | 11 months | The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". |
cookielawinfo-checkbox-necessary | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". |
cookielawinfo-checkbox-others | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other. |
cookielawinfo-checkbox-performance | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance". |
Recaptcha: _GRECAPTCHA | Session | reCAPTCHA Enterprise sets a necessary cookie (_GRECAPTCHA) when executed for the purpose of providing its risk analysis. |
viewed_cookie_policy | 11 months | The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data. |
Cookie | Duration | Description |
---|---|---|
Calendly: __cfruid | Session | This cookie is a part of the services provided by Cloudflare - Including load-balancing, deliverance of website content and serving DNS connection for website operators. |
Calendly: _gid | 1 day | Registers a unique ID that is used to generate statistical data on how the visitor uses the website. |
Stipe: private_machine_identifier | 1 year | Identifies the computer across login sessions and users to prevent fraud |
Stripe: m | 2 years | For fraud detection. Helps Stripe assess the risk associated with an attempted transaction on the your website. |
Cookie | Duration | Description |
---|---|---|
Google Analytics: _ga | 2 years | Google Analytics identifies unique users across GA sessions through client ID. The client ID is stored in the Google Analytics cookie. The GA cookie is set when a person visits your website for the first time. Google Analytics sends the client ID with each hit to associate hits with a user. |
Google Analytics: _ga_* | 2 years | Used to persist Google Analytics session state. |
Google Analytics: _gac_gb_* | 90 days | Contains campaign related information. If you have linked your Google Analytics and Google Ads accounts, Google Ads website conversion tags will read this cookie unless you opt-out. |
Cookie | Duration | Description |
---|---|---|
LinkedIn: _guid | 90 days | Used to identify a LinkedIn Member for advertising through Google ads |
LinkedIn: AnalyticsSyncHistory | 30 days | Used to store information about the time a sync took place with the lms_analytics cookie |
LinkedIn: bcookie | 2 years | Browser Identifier cookie to uniquely identify devices accessing LinkedIn to detect abuse on the platform |
LinkedIn: lang | Used to remember a user's language setting to ensure LinkedIn.com displays in the language selected by the user in their settings. | |
LinkedIn: li_gc | 2 years | Used to store consent of guests regarding the use of cookies for non-essential purposes |
LinkedIn: li_mc | 2 years | Used as a temporary cache to avoid database lookups for a member's consent for use of non-essential cookies and used for having consent information on the client side to enforce consent on the client side |
LinkedIn: liap | 1 year | Used by non-www.domains to denote the logged in status of a member |
LinkedIn: lidc | 24 hours | To facilitate data center selection |
LinkedIn: lms_ads | 30 days | Used to identify LinkedIn Members off LinkedIn for advertising |
LinkedIn: lms_analytics | 30 days | Used to identify LinkedIn Members off LinkedIn for analytics |
LinkedIn: sdsc | Session | Signed data service context cookie used for database routing to ensure consistency across all databases when a change is made. Used to ensure that user-inputted content is immediately available to the submitting user upon submission |
LinkedIn: UserMatchHistory | 30 days | Used for id sync process. It stores the last sync time to avoid repeating the syncing process in a frequent manne |