Jiratech

What evidence can you share that demonstrates the impact of the engagement?

They understand our needs to reach objectives, not just to tick some boxes. Also, they have a level of autonomy. When there was an issue, there wasn't just an issue. There was also a solution. 

They're also proactive, and this makes me relaxed. It gives me peace of mind because they understand that we need to have a sellable product, and they act accordingly. 

Radu isn’t just there to tick boxes from a to-do list. He has the mentality of clearing the path. If something might be a problem, he wants to fix it before finding out if its a problem or not. 

How did Jiratech perform from a project management standpoint?

All the activities are broken down by Radu and his colleagues into their actual assignments. We only zoom in on any divergence between what is written down and what actually has to be done if there's a discrepancy. But, most times that really isn't the case. For day-to-day communication, we use Slack because we don't share an office, and we meet two times per week.

They have a flexible payment plan. We structure our work into two streams based on dependencies per-day. Basically, on the stream that’s more unpredictable, they track their time. We have an agreement about a batch number of hours. Basically, we sign off on 200 or 300 hours on each continuation of the contract.

Within each of these periods, they keep their own time tracking, and I do some reviews, but there's never been any significant divergence. On the Knosis team, they have more autonomy internally and they don't depend on external things. We have a similar agreement for that team, only they deliver a fixed price exhibit. 

One thing that was very important for me and them was to have at least a three-month horizon of visibility on future work. We want to know exactly the order of the functionalities and the priorities. They always know the future scope of the work at least two, but preferably three months in advance. 

The principle between us is to always to keep a balance and visibility. For example, if they know that they’re going to need to bill more, they tell me in advance so I can take on a new customer myself. If you know that you're going to have two colleagues free for the next two months, tell me in advance, so we can do something about it. This sort of mutual flexibility makes things run smoother. The downside is that maybe they won't be able to scale as fast as is needed.

Are there any areas they could improve?

I think that one of the areas of improvement is that sometimes they're too optimistic. But, that is more of a piece of potential than a liability (if it’s managed correctly). 

Sometimes, especially because all the machine learning technologies are new and the frameworks are undocumented, they assume with optimism that there's a solution. They assume ideal conditions. Or, they assume that the solution will always work or that it's always documented. This optimism makes them sometimes underestimate how hard it will be to solve the problem. 

Do you have any advice for potential customers?

The clearer the requirements and the expectations of a potential customer, the more likely it is for Radu and his team to be able to deploy the full scope of what they can do. 

Basically, if they get a little bit of context and they are put in a story with an objective in mind, not just a list of functionalities, they can really think outside the box. So, that's what I would emphasize as a recommendation.