📆 onboarding #2 begins July 01 2024
Enterprise-Grade
AI Agents
We build private, personalised AI agents to the specifications required by enterprise so that professionals can fully harness the power of AI.
About

AI Agents Built For High Performing Professionals

According to Harvard Business School, AI improves highly skilled worker efficiency by +25.1%, productivity by +12.2% and work quality by +40%.1
It is clear that those who leverage AI win - and yet AI hasn’t to date achieved ubiquity in enterprise.

We started Superficial to get AI into the hands of every professional so that more people can benefit from the power of AI in their work.

We do this by solving what is holding back widespread enterprise adoption today.
1 Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality, Harvard Business School, 2023.
Our solution

Fully Private & Confidential

The number one concern holding back enterprise adoption today is leakage of confidential data.2
solution
All confidential personal and organisational data is masked and never shared with any third party or used to train any underlying model.
Users can converse privately with their agent, with data deleted immediately and not used for agent training.
All conversational data is deleted within 24 hours, no compromise.

Individually Tailored

Large Language Models (LLMs) are jacks of all trades, but masters of none, with limited domain specific knowledge.
solution
We build and train custom agents for individual users based on their specific roles and responsibilities, leveraging best-in-class, role-specific training content.
Users and their organisations can further train their agents on their proprietary data to create agents that are experts in their organisation.
Agents have memory and learn from conversations with their users, becoming more individualised and personally helpful over time.
We leverage multiple LLMs and choose the best for the job at hand, so you're not limited to any single provider.

Hands On Training

AI, like any new technology, succeeds only when users know how and when to use it best.
solution
We deliver on-site training to all new users before they're provided with their agents.
We provide follow up on-site and ongoing virtual training for all users.
All agents come with access to our Prompt Library - a resource with useful, role-specific prompts added by us and our community to help users get the most from their agents.

Staged Deployment

As with any new technology, adoption will stall without the right internal buy-in, engagement and delivery model.
solution
We start small and scale up, enforcing POCs with small internal groups before wider roll outs.
We require user opt-in. Only those that are interested in participating are invited to join.
We deliver top down. Adoption and usage increase and outcomes improve when staff are supported by their leaders.
2 As AI Advances, Trusted Data and Security Concerns Grow – Salesforce Report, Salesforce, 2023.

Our Deployment Process

Process
Step 1

Request Call

We work with only a small group of companies at any given time and onboard new professionals in scheduled cohorts.

Our goals for this step are to:
Understand your organisation and goals
Agree on a proof of concept structure and go forward strategy
Step 2

Deliver Proof of Concept

We recommend an initial fixed price, fixed term proof of concept with a small leadership group of between 5-10, before commencing with a wider roll out.

Our goals for this step are to:
Uncover any company-specific requirements to tailor our roll out
Get leadership buy-in to support deployment
Deliver real, tangible benefits to users within the POC
Step 3

Hands On Training

No user gets access to their agent without completing onboarding training.

Our goals with this step are to:
Set a base line of understanding of AI and our agents
Embed agents as part of users' daily routines
Set users up to be champions to support wider company adoption.
Step 4

Phased Roll Out

Users are onboarded in scheduled cohorts, with each cohort trained and supported throughout.

The goals of this step are to:
Roll out agents to opted-in users and achieve adoption and usage goals.
Provide ongoing training and hands-on support to ensure continued adoption and usage goals are met.
Uncover learnings to continually improve usage and outcomes.
our blog
We write regular articles on artificial intelligence and improving how we work.

Go to Blog

22
May

The Rise of AI Lobbyists in Washington: What It Means for Enterprises

The growing influence of AI lobbyists in Washington is reshaping regulations and policies, with significant implications for enterprises using AI technology.
Read Article
16
May

OpenAI Unveils Enhanced Model Specification for Improved AI Performance and Safety

Discover how OpenAI's latest model specification enhances AI behaviour and safety, ensuring optimal performance and ethical standards for businesses.
Read Article
13
May

The Unexpected Virtue of AI Hallucinations

AI hallucinations, often seen as errors, can become powerful tools for innovation when properly managed. Discover how Superficial leverages multiple models to balance creativity and accuracy, enhancing user experiences across various sectors.
Read Article
6
May

What Every CEO Should Know About Generative AI

Generative AI is revolutionising industries with its unprecedented capabilities, enabling businesses to streamline processes, enhance customer experiences, and unlock new opportunities. This blog post explores the essentials of generative AI, its practical applications, and strategic insights for CEOs to effectively leverage this transformative technology.
Read Article
📅 Onboarding #2 begins july 01 2024

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