“They responded right away, even when customer feedback changed our direction” — Two years through a pivot, supporting the launch of an enterprise SaaS

SkillAX is a product for enterprises that supports digital talent end to end — defining skills, assessing them, and helping people grow. More and more companies are starting to certify and develop AI talent internally, and that is what we support.

What sets it apart is that it assesses skills accurately. Who to give which work to, and where to invest in development — those decisions start with an accurate picture of people's current skills. That is why we care most about measuring accurately. We also define skills in much finer detail than other products, so it can be customized for each company. Going forward, we want to expand the features that support individual growth as well.

That is why the assessment is where we put the most effort in development. With AI, it looks easy to generate questions. But whether those questions really measure ability accurately, and whether people find the results convincing, is much harder. Unless we can guarantee that, users won't keep using the product.

I am the PM for the whole product. Besides managing the development members, I now also work in customer success, so I deal directly with customers, including onboarding support.

I work on development as an engineer. In SkillAX, we don't leave question writing entirely to AI — there is a step where people check the quality. I started out in that quality assurance step, and my scope in development has gradually grown from there.

There was a discussion inside the company about launching a new product around talent development. AI had become usable in all sorts of situations, and developing AI and DX talent had become a major trend. On top of that, ever since Hana-chan (our earlier consumer product), we had felt the need for a product that "widens people's possibilities." That was the background.

The biggest reason we asked micata was the relationship we had built on Hana-chan. We redefined the business for enterprises, where demand was strong, building on what we had learned from consumers with Hana-chan — and they took over the work as it was at that moment. I already saw them as a company that was strong at launching businesses quickly, so I felt comfortable leaving it to them.

I think the direction — "let's start with skill assessment" — had been decided. But the actual features had not been clearly defined. We built them up from there, aligning on the vision and direction as we went.

Above all, they moved fast. When we asked for a change of direction based on customer feedback, they responded immediately, and I was really grateful for that.

I think micata's strength was that they could do everything — design, infrastructure, and backend. APOLLO handled the AI core, and micata handled the application that delivers it as good features and a good experience. That division of roles let us combine each other's strengths, and it worked really well.

From the launch phase, we designed the testing approach and quality standards together and kept improving while verifying. Having them think it through with us made a big difference in raising quality without slowing down.

Full rollouts and trials are under way at major manufacturers and financial institutions.

What customers value most is that, compared with other products, the assessments are high quality and evaluate people accurately, and that the product can be customized to their own company's skills.

We are also developing an AI agent right now, and we show the features in development to companies as we go. Some have told us there is no other software like this. I think they appreciate how we dive quickly into new things and keep building features.

We are also continuously expanding the admin features based on customer feedback.

I think it comes down to the quality of the assessments. Companies want to develop AI and DX talent, and SkillAX's ability to "measure people properly" matched that need well.

The companies that have adopted it — both the organizations and the participants — are approaching it with a lot of energy. Working with companies like that is enjoyable for us, and we are grateful for it.

We want to grow the product around its strength of judging and diagnosing skills accurately. Right now we work on two fronts — skill assessment and building knowledge through learning — but we are also looking at assessing soft skills, assessments in the form of conversations with an avatar, and making use of data from talent management systems. We also plan to expand beyond the current AI and DX skill areas.

We plan to put together the best development setup as we expand the features. When it is time to build new features, we may well reach out to micata again.

These days, with AI, you can build things quickly even without much engineering experience. Even so, developing quickly while ensuring quality is still hard to pull off. micata develops quickly while making proposals across infrastructure, backend, and design, so for companies that want to build a good app fast, I think a company like micata is the best fit.

Companies that want to launch something new, and launch it fast. I think the biggest point is that they can develop quickly by reusing libraries and know-how built up on other projects.