Bob: The AI career coaching solution

An unprecedented number of low-wage workers are unemployed due to the pandemic - yet even before covid-19, low-wage workers struggled to access high-quality jobs. Many resources exist to help workers pursue better careers, but finding the right programs for one’s unique needs is challenging.

Personalized coaching is effective in helping workers navigate the workforce system. However, it’s difficult to provide coaching at scale, especially during a pandemic. We built Bob to address this need.

Bob is an open-source AI solution that serves as a navigation tool and digital coach for workers, and as a support solution for job coaches. Bob’s algorithm matches workers to the most relevant career resources and wraparound supports for their needs, enabling workers to navigate the resources more successfully and job coaches to quickly identify targeted support for workers. 

Bob has impacted 250,000+ jobseekers in Europe, and we are excited to “introduce” Bob to the US.

Over 53 million Americans are stuck in low-quality jobs that offer low wages, no benefits, unpredictable schedules, unsafe working conditions, and limited advancement opportunities. In particular, women, Latinx/Hispanic, and Black workers are overrepresented in this population. Workers are increasingly responsible for navigating their own career paths, and this is especially challenging for low-wage workers who face many barriers to accessing high quality, fulfilling careers. Such barriers include lack of actionable information about labor market trends like automation, negative past experiences with the education/training system, and limited time and money to spend on building new skills amidst increasing disinvestment in the low-wage workforce among employers.

Any opportunity to break out of the cycle of low-wage work has been shattered by the pandemic, which has led to staggering job loss among low-wage workers.

Though not a panacea, personalized coaching has shown to be effective at helping workers navigate the workforce system in order to pursue high-quality jobs. However, coaching is difficult to deliver at scale. The pre-pandemic workforce system was already strained, and now faces an overwhelming number of workers who need coaching.

The workforce system must leverage technology to provide coaching to workers at scale, and Bob can fulfill this need.

Bob’s algorithm combines labor market data, job coach logic, and key user data to provide an assessment of the user’s career goals and propose an action plan to pursue upskilling and a high-quality career pathway. Because advancing one’s career takes time, Bob complements this action plan with personalized coaching messages to provide additional resources and motivational support. Recognizing that just finding a job is not enough to ensure stable employment, Bob also matches the worker to wraparound supports, such as childcare assistance. Bob’s empathetic tone and advice are grounded in user research, positive psychology, and behavioral economics best practices. As a result, Bob’s advice is targeted, high-impact, and scalable.

Bob also supports job coaches by providing an automated assessment of the beneficiary and a “menu” of the most relevant workforce programs and wraparound supports for their needs. Through our user research, we’ve learned that knowledge of workforce programs often “lives'' with individual job coaches, and this is especially challenging given the high turnover among job coaches. With Bob’s personalized advice, job coaches can spend more time coaching beneficiaries rather than looking up workforce programs. Bob also provides dashboards for job coaches to track beneficiaries’ progress and broader impact metrics.

Our target population is low-wage workers. We have engaged them from the beginning of Bob’s development through a first-of-its-kind partnership with the French public employment system. When scaling to Belgium and the UK, we’ve continued to partner with public employment institutions to conduct user research and adapt Bob to user’s needs. We have already started adapting Bob to the US, and with MIT Solve’s support, we are excited to partner with a workforce board to conduct user research on low-wage workers, particularly workers of color.

With each new partnership, we interview target beneficiaries, build personas around subsets of beneficiaries, and develop content that addresses our users’ diverse needs. We continuously analyze user feedback and monitor how users engage with Bob in order to improve the tool.

Bob’s coaching system addresses low-wage workers’ needs by presenting labor market information in a personalized manner, outlining actionable steps to reach their goals, and sending regular motivational messages to stay on their path. Bob also responds to broader needs of low-wage workers, such as stable housing, by matching users to wraparound services.

Navigating one’s career can be daunting and lonely, and Bob serves low-wage workers’ needs by providing a clear plan and ongoing encouragement.

There are a myriad of skill-building programs and career resources available to workers, yet workers struggle to navigate and access the vast array of services. Moreover, pursuing an upskilling program can be daunting, particularly for low-wage workers of color who may have had negative experiences in the education/training system.

Bob empowers low-wage workers with information on career pathways, enabling them to make informed decisions about their career. Bob also increases low-wage workers’ access to high-quality training opportunities by identifying programs that match their needs and goals. Finally, Bob’s motivational messages help vulnerable workers feel confident in their abilities.

We are planning to expand to 3-5 states within the next year. We are in active discussions with public sector leaders in three states to adapt and deploy Bob. We have also conducted a market assessment to identify additional states and specific partners within these states to target. This process involved benchmarking state workforce strategies, identifying states that received funding for workforce innovation, and mapping out our connections with workforce leaders in each state. We are also monitoring workforce innovation funding sources, such as the T-3 Innovation Network and the upcoming re-authorization of WIOA. We are working to ensure that we are well-positioned to tap into these networks and funding sources. 

Through our market research, we have found that states face a dual challenge of addressing massive unemployment while simultaneously adapting their workforce services and programs to be offered virtually. The pandemic has created a strong need for tools like Bob to enhance digital service offerings and relieve the strain on workforce systems. The potential partners we are in discussions with are especially excited about Bob’s ability to provide more touchpoints with beneficiaries than would be possible with a human coach. Bob can also diagnose beneficiaries’ greatest challenges in upskilling and pursuing a career path, and triage beneficiaries to human coaches depending on their level of autonomy and the magnitude of their needs. These use cases, and many others, have generated strong interest among our target partners and we are confident that there is a strong market opportunity for Bob.

12 full-time staff

Promoting equity is central to our mission, our product, and our internal operations. We integrate DEI into all aspects of the employee experience, from recruiting to retention and rewards.

In order to build a diverse, equitable, and inclusive organization, we ensure our recruitment process is accessible to diverse candidate pools. We have also adopted policies and practices to reinforce DEI values on a day-to-day basis. We maintain a non-hierarchical structure where all employee contributions are equally valued. We also ensure pay equity through full salary transparency and clear compensation standards that result in minimal differences between senior and junior team member’s salaries. In addition, we strive to have strong representation of women and people of color on our Board and leadership team. Finally, we recently appointed a People Operations Manager who will ensure that we live and work by our DEI values going forward, as we continue to grow.

There are many solutions that match workers to jobs and career paths - but this only addresses one side of the challenge: awareness. Third-party research and our user research show that simply making workers aware of pathways is not empowering and does not result in meaningful change because these solutions do not address the underlying barriers workers face.

Our users have reported that regular coaching and encouragement is a key missing link between awareness and sustained action. While there are a handful of other coaching tools, such as Pairin and FutureFit.AI, we believe that Bob stands out in the way it leverages human job coaches’ logic and incorporates an empathetic, human tone.

Bob is unique because it synthesizes data and human job coaches’ expertise. Through hundreds of interviews with job coaches, we captured their logic when advising workers, and we built this logic into Bob’s algorithm. We are not aware of any other organization that has taken such an approach. As a result, we have modelized a unique “road to job recovery” methodology that provides effective, tailored advice for workers. We also recognize that low-wage workers need more than just a job to improve their wellbeing, and this is why we have incorporated wraparound services into Bob’s advice.

Bob’s interface and tone also stand out among our peers. We have learned to present career advice in a way that is actionable and empowering for workers, and our deep understanding of the challenges workers face is evident in Bob’s empathetic tone.

The core technology underpinning Bob is Artificial Intelligence. Bob’s AI was built by collecting the expertise of job coaches to create an expert system based on a diagnostic engine and solutions matching algorithm. Bob collects key information from the worker through an initial questionnaire that covers topics such as the worker’s demographic information, career goals, and the unique challenges they face in pursuing a career path. Bob’s AI processes this information, along with labor market data, to provide users with: (1) a diagnostic of their barriers to employment, (2) data-driven strategies, including career advice and wraparound services, to overcome these barriers, and (3) ongoing personalized coaching that includes encouragement, reminders, and resources to make progress on one’s strategies.

In order to match workers to relevant resources, Bob leverages a database of 100+ advice modules and 500+ programs and resources. We work with our partners to update this database with high-quality local/regional resources available to workers, such as apprenticeship programs, childcare assistance, and job fairs. These resources are categorized into advice modules, which are the basic units of Bob’s coaching. When Bob’s algorithm ranks a specific piece of advice highly, Bob displays relevant resources that will help the user act on the advice. Bob’s algorithm ensures that all advice and content shared are specific to the worker's needs.

In addition, we use state-of-the-art security technology - including encryption, document isolation, and Transport Layer Security-based protocols - to ensure user information is protected above and beyond the industry standard.

We measure the success of Bob’s AI by the relevance and level of personalization of Bob’s advice, and by the outcomes for workers. After coaching more than 250,000 workers to date, Bob has achieved the following results:

• 88% satisfied with the relevance of Bob’s advice
• 80% report that Bob’s advice is equally or more personalized compared to a human coach’s advice
• 41% found a job or pursued further training within 3 months of using Bob (compares favorably to beneficiaries who worked with a human coach)

Bob’s technology also has a positive impact on our public employment service partners by increasing their digital capabilities - an especially critical impact in light of covid-19. For example, our partnership with Belgium’s public employment agency demonstrated Bob’s capability to: 

• Assist beneficiaries on “day 1” through Bob’s digital coaching, rather than have them wait 4+ months for an appointment with a human coach
• Save job coaches’ time and improve their productivity by automatically matching beneficiaries to the right career supports, and generating a personalized action plan for each beneficiary
• Easily track program outcomes and beneficiaries’ progress towards their career goals

Finally, Bob’s technology amplifies the impact of external partners. Bob accomplishes this by aggregating high-quality workforce programs offered by service providers, and matching the worker to the programs that best fit their needs. Through this solutions matching, Bob enhances the service providers’ impact by enabling them to reach the specific workers who most need their services.

We aim to solve the problem of low-wage workers lacking the support they need to successfully navigate their career and access high-quality career pathways. Third-party research - and our user research - demonstrates that individuals struggle to understand labor market conditions, accurately assess their skill level, and plan and execute the optimal career planning and upskilling activities. This leads to more than 50 million individuals stuck in low-wage jobs.

In our desired state, all workers would have equal access to the information, resources, and support they need to access training and high-quality career pathways.

Research demonstrates that employment services like coaching are effective at empowering and guiding workers towards better career pathways. Researchers also find that labor market data should be presented to workers in a simple and personalized manner to achieve maximum impact. However, to be effective, employment services must be widely available and easy to use, and this is a challenge for our overstretched workforce system.

We built Bob to provide these employment services at scale. Our inputs include human coach expertise, labor market data, behavioral insights, and user research.

Bob helps low-wage workers to achieve the desired state by providing the following outputs: (1) presents labor market data in a personalized, actionable format; (2) makes it easier to access the most relevant training programs, career resources, and wraparound support; (3) provides ongoing encouragement and motivational support.

In the short-term, workers who use Bob are more able to access the resources and training they need in order to pursue better jobs. These workers feel more empowered because Bob provides an explanation for why they are receiving specific advice. Our user research has shown that workers feel more empowered when they are given a rationale, rather than just directed to do something with no clear reason.

In the long-term, we aim for Bob to contribute to systems change by increasing worker power, reducing occupational segregation, and promoting equitable economic opportunity. We believe that Bob’s model will inspire social service providers to engage with low-wage workers in a dignified - rather than disempowering - manner.

Source: https://tinyurl.com/y3dn3c9p

Our long-term goal is to scale Bob across the US through innovative partnerships with workforce organizations. We have active discussions with several states, and the validation pilot is the ideal opportunity to secure our first US partnership.

Within the next year, we plan to implement Bob with 3-5 partners, reaching 750k-1 million workers. We will develop a repeatable deployment model based on this initial cohort. Key activities will include:

• Develop a playbook for adapting and deploying Bob
• Conduct academic research (e.g. RCT) to document Bob’s impact, and publish findings to advance the field
• Establish a US Advisory Board
• Iterate on Bob:
  • Identify opportunities to integrate Bob at more stages of workers’ journeys
  • Provide recommendations to optimize human job coaches’ time allocation
  • Increase the number of languages supported

Within five years, we plan to implement Bob with 20-25 partners, reaching 8-10 million workers. To achieve these goals, we will:

• Continue measuring impact and publishing academic research
• Collect and analyze data for ongoing R&D and product optimization
• Iterate on Bob:
  • Expand functionality to serve user’s needs, such as retention support for incumbent workers
  • Create additional advice modules for specific populations, such as formerly incarcerated individuals
  • Continue refining Bob’s advice to address emerging labor market trends

Above all, as we scale and grow our network, we plan to use our position to bring low-wage workers’ voices and needs “to the table,” and advocate for systemic change that will improve the lives of low-wage workers, and in particular, workers of color.

Our main barriers center on two themes: data and distribution.

Access to up-to-date, relevant labor market data is a challenge shared by many in the workforce development ecosystem. There is currently very little data available that accounts for covid-19, and this has a clear impact on the reliability of Bob’s advice. We have already surveyed the US labor market data landscape and have confirmed that the essential data required to launch Bob is available. However, Bob’s advice is enhanced when we have access to even more granular, up-to-date data.

Our second barrier is achieving sustained distribution. We have developed a strong distribution model through workforce partnerships, and this has proven successful in the countries we have scaled to thus far. However, the success and speed of these partnerships relies on the level of engagement and the speed of decision-making among our partners. Public sector and nonprofit organizations are not always the most agile, and this can be a barrier to scaling Bob. Moreover, even if we have partnerships in place, it can still be challenging to enroll workers onto Bob’s platform if Bob is not fully integrated into the way workers engage with the partner organization. For example, it may not be enough to simply make Bob available on a workforce board’s website. Rather, we may need to incorporate enrollment in Bob with the unemployment insurance process or other universal entry points where workers interact with the workforce system.

To overcome the data barrier, we have identified a partner (Chmura) that can provide the data we’re looking for. However, there is an upfront cost, and funding through MIT Solve would help us secure this data. As we scale over time, we plan to share the cost of the data with our partners, and seek philanthropic funding as needed to cover any gaps. 

More broadly, we are committed to helping our workforce partners improve their data tracking and reporting capabilities. Not only will these efforts enable us to improve Bob with better data, but it will also strengthen the capacity of the workforce field.

To overcome the distribution barrier, we are drawing on our experience in Europe and have already documented a deployment methodology and change management strategies to enable our workforce partners to seamlessly implement Bob. We have also built Bob’s technology in a manner that is easy to integrate with our workforce partners’ technical infrastructure and processes. In addition, we hired a new US Country Director who brings experience in and connections with the US workforce development system. We are identifying creative ways to accelerate our distribution by accessing emergency funding and WIOA discretionary dollars, and by creating pilot programs. Finally, with each new partnership, we will document beneficiaries’ user journeys, including all of the ways that they engage with the workforce system. This will allow us to identify and test the best entry points to enroll workers onto Bob.

As a data-driven organization, we place a strong emphasis on measuring Bob’s impact. We do this by regularly analyzing user data collected through Bob and tracking our impact over time. Over the long-term, we would like to conduct a randomized control trial to understand the impact Bob has on low-wage workers and job coaches. We have already begun working with labor economists from Yale University, George Washington University, and the University of Illinois to outline our research questions and design a study. Our next step is to secure sufficient distribution and funding to conduct the study. We have already received limited funds for the research, and MIT Solve’s support would be instrumental in closing this gap and accelerating Bob’s distribution.

Through this research, we not only hope to further improve Bob, but also advance the workforce field’s understanding of how technology can positively impact low-wage workers and job coaches.

We are a team of technologists, UX/UI designers, impact evaluation experts, and public servants. Our team of full-stack developers brings experience working in the public sector and at leading tech companies like Google. Our Partnerships team’s experience spans the public, private, and nonprofit sectors, including coaching incarcerated youth and developing upskilling programs for formerly homeless individuals.

In developing Bob, our entire team spent significant time with workers and job coaches to deeply understand their needs. We continue to stay close to those we serve through user research and by taking turns responding to our user’s questions and feedback.

Some of our team members have personal connections to the issues of unemployment and upskilling. Following the 2008 economic crisis, our COO’s mother experienced long-term unemployment. She faced many barriers, including her age, lack of credentials, and difficulty navigating the job search and upskilling process. Too often, she felt monitored and controlled by her job coach, rather than empowered and supported. Her experience has informed the way we built Bob to be actionable, empowering, and caring.

Émilie, a data scientist at Bayes Impact, witnessed the impact of upskilling on her mother. Émilie’s parents fled Vietnam during the war, and Émilie’s mom initially did not pursue education beyond the 9th grade. Eventually, she had the opportunity to enroll in Dental Technician training, and this had a transformative impact on her sense of self and her family’s well-being. Her story is a key driver inspiring us to enable access to upskilling through Bob.

SEI Ventures is our first partner in the US, and their funding enabled us to build a beta version of Bob for the US and to advance our distribution strategy. We are also partnering with Hope Street Group to conduct user research and develop technologies to support job coaches. In addition, we are partnering with labor economists to conduct research on Bob’s impact. Finally, we have received strategic advising through a number of networks and individuals in the workforce development space. These include Harvard’s Taubman Center for State and Local Government, MIT’s Good Companies Good Jobs initiative, DEI experts, and workforce board leaders. 

Our main partner in France is Pôle Emploi, and we formed a unique partnership to access beneficiary data and deploy Bob across France. We are also part of the Ashoka network, with our CEO being the youngest Ashoka Fellow in France. In Belgium, we have partnered with the public employment agency to implement Bob and build tools for job coaches. In the UK, we were selected for Nesta’s CareerTech Challenge to develop and distribute a UK version of Bob. To develop Bob UK, we are partnering with ACH, a social enterprise that specializes in refugee resettlement through labor market and social integration. Finally, we are supported by a number of funders, including Google.org and the Mastercard Center for Inclusive Growth, to invest in R&D and new upskilling features for Bob.

Bob serves a dual role as a tool for low-wage workers and for job coaches. Bob is free to workers and accessible from any computer or mobile device. Bob delivers value to workers by providing career advice and connections to wraparound services that will improve their wellbeing. We reach workers by partnering with workforce organizations to incorporate Bob into their processes and services for workers. We regularly collect metrics that are a testament to our impact, and we continue to iterate on Bob to amplify our impact.

Our other “users” are job coaches and the workforce organizations they are a part of. We provide value to job coaches by building back-end solutions through Bob. This includes dashboards to track beneficiaries’ progress, visualize labor market trends, and monitor impact - you can view examples of these tools here: https://tinyurl.com/y2q8jwhg. Rather than replace human job coaches, Bob augments their efforts by making it easier to manage their workflow and identify the most relevant programs and resources for their beneficiaries. This results in significant operational impact, allowing job coaches to be more strategic in how they allocate their time and resources. 

Our first revenue-generating partnership with Belgium’s public employment agency demonstrated the value that workforce organizations derive from Bob. Through this partnership, we worked closely with job coaches to digitize their processes and integrate Bob. We have received positive signals among US workforce organizations that indicate strong interest in our services and a willingness to pay for the value Bob brings.

Our goal is to achieve sustainable funding through our partnerships with workforce organizations. While Bob’s technology is open-source and freely available, we have discovered a need for support in adapting Bob to our partners’ local context, their technical infrastructure, and their business processes.

We offer Bob as a software-as-a-service product, where we charge a one-time fee for the initial adaptation and integration of Bob, and then an annual maintenance fee to update Bob’s data and features according to an established Service Level Agreement. If our partner is unable to cover the full cost of Bob, we will work with our partner to seek philanthropic funding to cover the gap. 

We have found that our partners not only derive value from the Bob tool itself, but they also benefit from the technical knowledge and skills we bring. For example, our partnership with Belgium's public employment agency went beyond simply implementing Bob to also include a full assessment of how the agency can leverage technology to automate certain processes and improve service delivery for its beneficiaries.

We have validated our revenue model in Belgium and conducted an initial market study in the US to assess demand and willingness to pay for our services. We are already in conversation with multiple state workforce agencies that are interested in Bob, and we are confident that we will be able to achieve financial sustainability within the next 2-3 years.

Much of our philanthropic grants are focused on supporting Bob’s R&D and distribution. SEI Ventures has provided our first grant specifically for our US strategy, and we are seeking MIT Solve’s support to further invest in our US efforts. As stated above, we are also cultivating sustainable revenue streams by partnering with workforce organizations.

Philanthropic Funding

Google.org

• Amount: $1,188,375 (€1,000,000) grant
• Date Awarded: January 2020
• Timeframe: 3 years

Mastercard Center for Inclusive Growth

• Amount: $517,500 grant
• Date Awarded: August 2020
• Timeframe: 18 months

Nesta

• Amount: $33,030 (£25,000) grant
• Date Awarded: February 2020
• Timeframe: 9 months 

Degroof Petercam Foundation

• Amount: $1,188,375 (€1,000,000) grant 
• Date Awarded: February 2020
• Timeframe: 5 years

SEI Ventures

• Amount: $250,000 grant
• Date Awarded: May 2020
• Timeframe: 2.5 years

Devoteam 

• Amount: $106,569 (€90,000) grant
• Date Awarded: April 2019
• Timeframe: 3 years

Revenue Generation 

Actiris (Belgium’s Public Employment Service)

• Amount: $154,488 (€130,000)
• Type: Revenue 
• Date Awarded: July 2019

Our ultimate goal is to raise $750,000 in grant funding over the next two years to support our US scaling efforts. This funding will enable us to build our US team, adapt and iterate on Bob for the US market, and achieve our distribution goals.

This catalytic venture philanthropy fundraising will play the same role for our non-profit as traditional venture capital investment plays for startups. Specifically, the investment will be used to finance the cost of further user research, product adaptation and content creation. It will also allow us to develop new coaching features and tools based on our user research. In addition, this funding will allow us to expand our Partnerships team, enabling us to accelerate our outreach efforts, develop a playbook for adapting Bob’s data sources and content for each new partner, and track the value and impact Bob has on workers and on our partner organizations. 

In the long-term, the revenue generated from partnerships will supplement our growth. However, in the short-term, our model is to leverage philanthropic funding for the initial R&D and product development for the US. We are strongly committed to transparency and open data, and using philanthropic funding allows us to develop open-source code that is freely available to anyone. This also ensures all technological choices are made in the sole interest of the target population of low-wage workers.

Our cost structure primarily consists of the human resources needed to develop partnerships with workforce organizations, adapt Bob to each partners’ local context, and integrate Bob with our partners’ existing IT systems. Our fixed costs include data costs, rent, and other standard overhead costs. Our variable costs include distribution of our platform (ads, promotion, marketing), project-related travel, and IT infrastructure (which can be covered through in-kind support).

Our estimated budget for 2021 is $770,00, and it is driven by our objective to deploy Bob in 3-5 states. This budget accounts for:

• Partnership and project management ($160,000, 2 FTE): developing partnership with workforce organizations, managing Bob deployment projects
• Product and content development ($220,000, 2 FTE): user research, content and coaching design, localization of advice modules, creation of wraparound services database
• Engineering ($250,000, 3.5 FTE): data research and analysis, AI and software development
• Operations ($65,000): data providers, user testing, IT, overhead, other service providers
• Distribution ($30,000): ads, platform promotion to beneficiaries
• Monitoring and evaluation ($45,000): conduct impact surveys, coordination with academics on evaluation framework design and implementation

This budget will be covered through grant funding already raised in 2020, ongoing fundraising efforts, and contract revenues from our partnerships. Grant funds will finance investment in product and R&D, while contract revenues will cover the costs of adapting and deploying Bob with each partner. As such, expenses and revenues will depend on the pace of Bob’s deployment.

We are excited to apply for the Challenge because the validation pilot represents a critical step in overcoming our distribution barrier. As Dr. Jackson writes, workforce boards are in a “prime position to drive impact at scale,” and we had previously identified workforce boards as a priority distribution channel when developing our strategic plan for scaling to the US. The validation pilot format shares many similarities with past partnerships we’ve had in Europe, and we believe this model will be the ideal opportunity to create our first “proof of concept” in the US.

In particular, we will leverage the validation pilot as an opportunity to better understand the specific barriers low-wage workers face in the US, as well as the constraints job coaches encounter. Though low-wage workers we serve in France, Belgium, and the UK encounter challenges related to inequality and systemic racism, we realize that American workers - and particularly American workers of color - experience these issues in unique ways. We are eager to establish a partnership that will allow us to delve deeper into the specific challenges American workers face. We will also leverage the validation pilot as an opportunity to map out beneficiaries’ user journey and identify the most opportune times to enroll beneficiaries in Bob’s coaching.

Finally, the MIT Solve network will be instrumental in supporting our distribution. The Challenge partners and our fellow Challenge applicants represent an unparalleled network that we would leverage to identify new partners and build more connections in the US.

As stated above, we rely on partnerships to achieve distribution, and we are always looking for organizations that would benefit from Bob or that can connect us with other potential partners to deploy Bob.

In terms of funding and revenue model, we are in the process of conducting a market study to analyze the competitive landscape, identify and prioritize potential partners, and benchmark our pricing model. We would benefit from the advice and mentorship of the Challenge partners in defining our revenue model and putting it into action.

We are establishing a US Advisory Board, and we already have a Board Chair. We are actively seeking additional members who can bring diverse experiences and skill sets. Finally, we have begun collaborating with labor economists to study Bob’s impact, and we are always looking for more partners to help us with monitoring and evaluation.

There are many organizations we would like to partner with to deploy Bob. We are targeting state workforce agencies, state and local workforce boards, workforce board associations, and non-profit organizations that operate Career OneStops (e.g. Goodwill, Jewish Vocational Services). We are currently in planning discussions with three states, and we are planning to target additional workforce organizations in Texas, Connecticut, Washington, and Rhode Island - though we are very open to working with other states where we are able to make connections.

We would also like to connect with national networks such as the National Fund for Workforce Solutions, the National Association of Workforce Boards, the Rework America Alliance, and the US Conference of Mayors. Connecting with these organizations will provide valuable insights into the latest workforce trends and challenges their members face. We also envision partnering with these networks to deploy Bob among their members.

Finally, we have connected with other workforce nonprofits, such as Generation and Hope Street Group, and we believe that there are many opportunities for Bob to support their work. For example, we are working with Hope Street Group to conduct user research and eventually build tools for their network of job coaches. Other non-profit organizations we would like to partner with include Opportunity@Work, Center for Employment Opportunities, Year Up, Project Quest, SkillUp, Credential Engine, and many others. We see opportunities to deploy Bob with these organizations, and/or leverage the content and programs developed by these partners and incorporate them into Bob’s advice.