Partnering with HumanFirst, Infobip generated over 220 knowledge articles, unlocked 30% of their agents' time, and improved containment by a projected 15%.
Reviewing the state of employee experimentation and organizational adoption, and exploring the shifts in thinking, tooling, and training required for workforce-wide AI.
With a one-click integration to Conversations, Infobip’s contact center solution, HumanFirst helps enterprise teams leverage LLMs to analyze 100% of their customer data.
Partnering with HumanFirst, Infobip generated over 220 knowledge articles, unlocked 30% of their agents' time, and improved containment by a projected 15%.
Reviewing the state of employee experimentation and organizational adoption, and exploring the shifts in thinking, tooling, and training required for workforce-wide AI.
The decision to build proprietary solutions or buy ready-made software is important for companies investing in a long-term digital vision and roadmap.
This is particularly true when it comes to AI/ML tooling, a field where advances in the last few years have made the “buy” option a strong alternative: maintaining in-house solutions becomes a pain, and not all departments are equipped with the proper resources to build home brew tools.
For companies competing on the NLU front, the need for tooling around exploring, labeling, and managing the underlying voice, text, and AI training data is becoming increasingly important.
In a "Build vs. Buy" decision, HumanFirst is a strong choice for enterprise teams, consistently meeting the considered criteria when choosing a SaaS provider. At the beginning of 2021, we pivoted towards cultivating an enterprise clientele and now have successfully onboarded dozens of enterprise customers (for more information on our enterprise clients and their use-cases, please contact us here).
Here’s a look into those considerations.
Six considerations when selecting your enterprise Saas software:
Handles long-term roadmap
Today, digital customer channels are generating data at a massive scale. According to Gartner, roughly 70% of these interactions with customers will involve emerging technologies by 2022. In the NLU space, this includes chatbots, virtual assistants, IVR, agent augmentation, analytics, and NLU-powered help centers. That being said, digital transformation journeys often start with only a few applications of NLU at a time. As enterprises expand their digital offerings, it is pertinent for business leaders to develop a strong, core understanding of their data in order to define a unified and integrated strategy.
Luckily, the underlying data used to develop and power these different use-cases is the same. Whether it’s a self-service chatbot, an NLU-powered help center, or a sophisticated analytics dashboard — teams need to gather unlabeled data from different sources (such as call center transcripts, chat logs, customer reviews, help center tickets, search queries, surveys & other qualitative feedback) and then label it to train NLU models deployed across different channels.
Dataneeds to be centralized in one hub to deliver consistent information across channels. The problem today is that different departments are handling the different data sources without proper communication and collaboration. Naturally, this leads to a partitioned strategy and slows down time to market, since departments aren’t leveraging each others’ resources to bootstrap their upcoming NLU applications. To accelerate digital transformation roadmaps, enterprise offerings should remove silos and give access to the same (and all) data throughout departments.
Creating cross-collaboration allows stakeholders to identify new opportunities and use-cases by re-using data as the digital transformation journey expands. For this type of evolution to happen, enterprises need end-to-end data-centric solutions. As an example, the proper tooling would need to improve the coverage and accuracy of the enterprises’ chatbot performance, as well as unlock insights into next projects. Once the NLU and underlying intents are understood, improved, and deployed on a chatbot, they can easily be used to develop analytics dashboards for contact centers, thus unlocking a new use-case.
Our vision is to build a solid foundation for clean, unlocked, and non-siloed data to power insights and experiences. HumanFirst understands the importance of accelerating every application where building accurate NLU is critical.
Handling variety extends to language as well. Since HumanFirst is multilingual, it supports up to sixteen languages, including: Arabic, Chinese-simplified, Chinese-traditional, English, French, German, Italian, Japanese, Korean, Dutch, Polish, Portuguese, Spanish, Thai, Turkish, and Russian. Gathering diverse training data is key to developing a comprehensive application.
Meets compliance and security requirements
Since the contents of your data may be confidential, we understand how important it is that your information is secure. Our background is security, and in our previous startup (PasswordBox acquired by Intel Security in 2014), we managed the personal passwords of millions of users.
HumanFirst applies top security practices throughout the entire application. Users remain in full control of their data, with everything uploaded to HumanFirst stored under Google Cloud's infrastructure. Data is always encrypted at rest using the AES-256 cipher.
Enterprise customers also have the option to run HumanFirst on their own cloud or infrastructure. HumanFirst supports fully air-gapped deployments for the most stringent security.
We also support completely customizable user permissions across namespaces and features. In terms of SSO, enterprises can use OIDC or SAML2 to control access from your existing enterprise SSO systems.
Provides API Integrations
In the current technological infrastructure of enterprises, it’s no longer viable to buy a product that is unable to work interoperably across functions.
HumanFirst offers flexible data ingestion and easy integrations through our APIs; our command-line interface (CLI) allows enterprise customers to easily integrate their data and work within HumanFirst in their development pipeline, by automating the creation of snapshots, git commits or launching evaluation reports with a single command line.
HumanFirst also provides the ability to plug in a 3rd party NLU provider (we currently support Rasa, DialogFlow and soon Watson) and can help integrate custom NLU models.
Offers Scalable Pricing
HumanFirst pricing scales with the amount of data processed and the number of seats, however, discounts are available for customers processing large volumes of data or to users who commit to yearly subscriptions. There are also markdowns for early-stage companies, startups, and nonprofits.
Provides Comprehensive support
A good vendor partnership defines success together. Our team is on hand to help you customize your projects. Once you sign up for HumanFirst, you have access to our personal slack community, where you have direct access to our dev and sales team. HumanFirst also provides custom training, development and data engineering services for enterprise customers.
HumanFirst Will Build for You
Don’t waste your resources building internal data management software. HumanFirst is enterprise-ready, filled with all the tools and capabilities that allow your team to discover, label, manage, and evaluate large-scale NLU data.
To learn more, check out our website here. You can also chat directly with our team here.
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