Name: DataStore Roadmap
Uploaded: 2026-05-06T15:30:22.554Z
Duration: 25 min 26 s
Description: DataStore Roadmap

Transcript for "DataStore Roadmap": Thank you. Thank you, Brittany. Okay. Welcome, guys. I just want to start off with the, a bit of it's going through the agenda. Henry's gonna give us a brief update on the company updates. Phil's then gonna give us a demonstration on the indexing client and some searching, and then I'm gonna go through some product vision and road map. And then I'm gonna finalize it all with the customer working group. And at the very end, we've got a q and a session. So, Henry, over to you. Yeah. Thank you. Thank you, Wayne, and thanks, everybody, for joining. I think I just took out, Brent's, hopefully, some of you, listen to Brent's comments earlier at the opening of the the original session. Just, I guess, to put this in context, obviously, MicheTech made the investment in high-tech, where Datastore came from, just over just about ten years ago. Mitratech has grown meteorically since then. So maybe some of you will be aware that Mitratech offers legal and HR solutions as well. Just to give you a sense, the GRC division that Brent is now CEO of and where Datastore sits, is larger than, Mitratech was when, it made the investment in in Datastore, in high-tech, let's say ten years ago. So because of that meteoric growth, we have been able to, split into this GRC division and make all the investments that Brent talked about in in the platform. And I think if we just go to the next I mean, let's say you can see that the stats and you will share these slides up afterwards in terms of, the size of the the organization now. But if we go to the next slide, I think probably the most important, element is and I want to reemphasize from what Brent said is, you know, the platform that, we've launched and we were talking about earlier is only as powerful as the legs of the stool, that that we that we have invested in. And so, yeah, whilst a lot of you are very familiar with, Datastore and some with Policy Hub that came with high-tech, Mitratech now has a wide range of other solutions and through the platform and through a lot of the AI work that we are doing and they is allowing our clients to, leverage more of the solutions, that Mitratech has. So I would, you know, if if any if there's any interest in any of these legs of the stool, any of these components on the wheel in front of me or interest, I would stress, you know, please do reach out to your your account managers to learn more and how, you know, they can they can, can leverage, what the investment you've made in Datastore as well. So that was really a a sort of a little brief update. What I want to do now is hand back to Wayne so we can we can concentrate on on, the Datastore updates. Thank you. Thanks, Henry. Okay. So I just wanted to quickly touch upon what the components the core components of what data store is. So data store is a purpose built enterprise content management solution for financial services designed to solve challenges for managing huge volumes of regulatory content under increasing regulatory pressure whilst being able to find the right information quickly. The will shows you that it works from end to end. So we can start the very top with CAPTCHA. So CAPTCHA brings information in across the organization in a controlled and compliant way, can move to index. Index has that raw content into governed information, classified and linked to business context. Retrieve ensures the right people can access the right content at the right time for operational work or regulatory requests. Report supports audits and investigations with consistent defensible package evidence. Integrate ensures that data store doesn't operate in isolation, which is really important, acting as a central backbone in connecting legacy systems and GRC workflows. Finally, secure. So that underpins everything. Handling high volumes of data safely, enforcing retention policies, and providing the resilience registry customers depend upon. Together, these capabilities give us an end to end control of information and form the foundation of everything we're investing in this year. I'm now gonna hand over to Phil for a demonstration. Thank you, Wayne. I'm just going to try and get the correct screen shared. And here we go. Give me a thumbs up or thumbs down. There we go. Okay. Yeah. I am very pleased to be able to give you a look at the first release of the web, web based indexing studio. With the web based indexing studio, we can still offer the ability to acquire, index, and store documents to Datastore only from the the comfort and the efficiency of your web browser. Starting with the login page I've got on screen here, we offer forms authentication, Windows authentication, and SSO. I'm going in with forms authentication so you can see the nice login page When I go in, you are presented with your document workspace. Your document workspace is basically a screen which gives you a list of the data definitions which you have permissions to be able to store documents against. This version allows document importing, so I'm gonna go ahead and choose one of my data definitions and start importing some files. So from this screen here, you have the option to basically browse and go and find, find whichever documents you want to be able to import like that. Alternatively, if you would prefer, you can use, Windows Explorer and drag and drop your files into the dialogue. If there's any erroneous files in there you don't want to report, you can simply ignore them or you can remove them from the list. Or if you've decided that you've chosen the wrong data definition to put your your, documents against, you can simply choose the correct one from the list above. So once you are happy, you can hit go and, Indexing Studio will go and get those documents and put them into the Indexing Studio like that. Once they're in here, they are available for you to work on, and you can probably see lots of features you would expect to see in in an application like this so that you can navigate through the pages as you, process in the document. If the orientation is wrong, you can mod it, you can rotate it around. If you want a little bit more screen real estate, you can basically you can have the fit to height. You can, fit to width. You can zoom in and out. You can go full screen. All very quick, all very snappy, and all within the comfort of your web browser. If you've decided that these documents are against the wrong data definition at this point, you can even choose the the documents you wanna move, choose to move, and then go and send it to the the correct data definition before you continue. That should do it nice and quickly like that. I go and have a look at my data definition. They are there now. Okay. So if I'm ready now to start indexing my document, the index fields over on this side of the screen here, and I can start putting in my index criteria. I'm not gonna populate the whole lot in the, interest of time, but I'll put in enough to be able to see what's going on. Also to assist with the indexing of of documents, we do support all your index assistance, which you will probably be used to with the domain thick client version of index in studio. To demonstrate that, for example, I have a, a barcode test, data definition set up here, which has a document within it, which has a barcode on it, like that. And so if you simply execute your index assistant against that against that, it should go away, read the barcode, and populate index fields. So this will work in the same way as your your, your your file index assistance or your your SQL lookup index systems or anything you've got like that, they will all work with the, the the Thin Client version as well. Okay. So, going back to my documents that I'm working on, so I've got my, my document here. What you will notice as well at the bottom, it says changes are automatically saved. This is because anything I'm doing with these this document, is automatically saved to the server. So the documents themselves are saved on the server, the index field values are saved on the server, and this is one of the major benefits of going to the browser based version. So let's say, for example, I'm processing a load of documents. I, just I run out of time. I have to relocate or move to a different office or something like that. All I need to do now is simply go to my my new office, open up a new browser, go into my Index Studio, log in. And once I've done so, it will give me access to all of those documents that I've been working on. So they're still there in exactly the same way. To maintain the integrity of these documents as well, what we also do is we also implement a locking mechanism. So, oh, I was working on this document in a different session a moment ago. So if I go and try and open this now, it has detected that I've already got that open somewhere else and it's warning me that I can't make changes to that without making a conscious decision to say, okay, I'm happy to proceed and unlock that document. So this means now that I've got access to that means now that I've got access to that document. You can see all the changes that I made earlier to it there, and now I've got hold of this rather than the the other session. Okay. We've all, done now. Let's say I'm happy with that document. I can go ahead and store that to Datastore simply by clicking the store button. That will send it up to the Datastore storage. So I've gone. And that will now allow me to go across to my searching clients and hopefully be able to retrieve that document. So I'm logged in. I'll go and find the search template, against which I can find that document. Hit go, and it should bring me back my search. Here we go. And there's the new document I put in there. For I know it's been out for a little while, but anyone who's not familiar with the web searching version of the searching client, they really should give us a shout because it's a fantastic piece of software. It's been out for a while, like I say, and it's now almost on par with the thick searching clients in terms of the functionality it offers. So you can do your searching, you can do your viewing, export and modification of field values. We've got document routing in there. You could open in native applications, print it. We've even got some features in here which are not available in the thick lines, like, for example, the ability to go and create a quick access link. So what this means is I can actually come in here and actually create a unique URL, which will give me access to the documents I'm viewing on screen. What this means is I can then send that, share that with anyone I want. I can bookmark it so if I want to come back to it later. But the bottom line is if anyone tries to open that URL, if they've got permission to do so, Datastore will take me straight to that document and be able to view that document by itself. And I'm sure you can imagine there's plenty of, of different kind of, like, functional, you know, options, made available with with this kind of feature. Okay. So I know it's very quick, but that's all I've really got to show you in in this period of time. If anybody has any questions about this or wanna see anything further, just give us a shout, and we would be very happy to jump on and give you a much bigger demo. Thank you. I'm gonna stop sharing now. I'm gonna pass back to Wayne, I believe. Thanks, sir. Okay. So I just wanna give you a bit of an an update on product vision and road map. So I'm gonna start off with the twenty twenty six initiatives, if that's okay. So this slide shows how we're thinking about data store in 2026, anchored around six strategic initiatives rather than a long list of features. So information life cycle control is about owning the the full journey of regulatory content from capture to governance. Trust and system of record ensures that data store is authoritative, defensible, source for customers and systems that they rely on. Governance and risk assurance closes the compliance gaps and builds audit confidence. Accelerated information access reduces friction so people and systems are able to get what they need faster. Intelligence, content, insights, and automation, this is where AI comes into play, is actually about improving outcomes, not just for the sake of putting AI inside the application itself. And scalable and resilient platform ensures that data store can grow with the GRC platform securely and reliably. Together, these six initiatives give us a stable strategy that connects the road map to the customer story. Perfect. I'm just gonna touch upon, the candidates as well. I am gonna spend a little bit of time on AI. It's, probably of no surprise, but just I'll get through the candidates, and I'll explain a little bit more. So this slide maps out our six initiatives into Con Key 2026 investment. So on the ingestion side, as you've seen, we're building a web based indexing client for both import and scanning. So you've seen import today. Moving away from the desktop tooling, we're aligning with a web first direction. For trusted system record, we're advancing our web based search and access to make index content easy to find and rely on. Governance and risk assurance is addressed through resolving high priority issues and functional gaps, which we're on with right now, hence the reason for the orange text. I just lost my space now. Right. The rest APIs for thick client opens up integration extensibility, so reducing friction where data store connects into the broader workflows. We're also running two proof of concepts, one one around AI assisted document indexing to explore smarter ingestions and insight extraction, and then also hosting support to give us and validate the, flexible deployment options. Together, these are a pragmatic targeted investment that moves data store forward without overcommitting. So what I'm gonna do is just touch a little bit about the, doc I'm gonna call it document intelligence power and automation. So this effectively is our AI. So over the last few months, we've been undertaking a structured discovery exercise across the customer base, speaking with customers, reviewing how customer how data store is being used in practice, and looking at where the platform is and isn't delivering value as it could. It's not a sales exercise. It's a genuine attempt to understand what problems you face day to day and to make sure that when we what we build next is grounded in reality rather than assumption. So what I'm gonna share with you today is what we found, what we're proposing to do about it, and what it can mean to you commercially. Oh, that's not come up very well too, has it? Okay. So you're gonna have to trust me on this one because I'm not quite sure what's going on there. Okay. So this slide summarizes what came out as part of discovery work. Across the customer across customers, we engaged with five consistent problems that emerged. This heat map shows how strongly each one was felt. Manual and inconsistent indexing, key information traps within documents, search and retrieval limitations, high levels of manual effort, and limited visibility leading to reactive rather than proactive operations. What was struck was our consistency. So these weren't isolated issues. These were all things that we found across the board on every customer that we spoke to. Okay. Perfect. So I'm now gonna talk to you about our six pillars. So so what we're proposing to do about it remember, this is a proposal. So what we're looking to is build a set of capabilities called the document intelligence power and automation. It's a catchy title. It's all structured around six core pillars. Starting with document intelligence, automatically classifying and tagging and enriching documents as they arrive. Moving into information extraction, so that's pulling pulling values directly from documents as structured data. Document insight, surfacing critical facts without users needing to open documents. Case intelligence, understanding the completeness and the current position of a case or record. Intelligent route and orchestration, so that's really using intelligence to drive workflows automatically. And finally, operational intelligence, giving you real time visit, they see what's happening across everything. The important thing to understand is these aren't six separate products. They're progressive model that layer upon each other from, on from the one from the last, moving document understanding through to full operational automation and control. This isn't gonna come out very well either. Right. So, this slide connects we're doing this slide connects where we have identified problems to capabilities. What we're and what we're proposing. Each problem has a primary pillar assigned to it. The secondary pillars that contribute alongside it. Inconsistent indexing is addressed through document intelligence. Information traps inside documents through information extraction, search limitations through document insight, high manual effort through document routing, and limited visibility through operational intelligence. The mapping is important. It means that we're not building capability speculatively. Each pillar has a clear problem it's designed to solve validated through discovery work that we've undertaken with you. Okay. So I wanted. to take you through sort of a pragmatic, approach to this now. So this was based on a customer we spoke to who basically is is processing around 15,000 documents. So just to bring it to life, we modeled on what it could mean for a customer processing 15,000 documents a month manually. So each document taking roughly about two minutes to index. So in total, that's around five hundred hours of manual effort every month purely spent on indexing, roughly equivalent to four full time equivalents. So by using AI to automate 80 of the volume, which we think is quite low, we could reduce manual effort by over four hundred hours a month. At at AI processing costing 7p per document, which is expensive, just using this as a pragmatic approach, the annual saving would still be around £147,000. So that's a 7073% reduction in in your cost. But beyond the financials, document intelligence enriches metadata beyond what staff would typically cap capture. One thing we did get is that staff tend to get through indexing quickly and and just put in the bare minimum. But, actually, if you think about your users come back to the document, actually have to click on it to find the information they're looking for, If you captured that at the point of index, then it would definitely cost more money or take longer to do to do it. So this provides stronger compliance and a platform that scales with the volumes as you grow without growing your headcount proportionally. One thing I'm gonna make a plea around, though, is the next slide. So some of you, would have been around some of you have been invited to complete a survey. Everyone's gonna be completed, asked to complete a survey. That's really important for us to baseline where we can get to from the AI perspective. It will allow us to understand how you consume the application, things you find difficult, and actually allow us to focus the effort on where we build the the piece of AI into the the product itself. So we're at a very early stage with this, but we need your input. You'll receive that short survey. It only takes about ten minutes to to respond, and your responses will directly inform the road map as we go forward. Right. Just a few more from me. So I'm just gonna talk to you about the customer working group. So to kick it off, we have two suggested topics for the customer working group, and I will cover what the customer working group is in a moment. So the first is obviously AI. I've given you sort of six flavors for how we think based on the problems that we've we've found that we could use AI, but these can come from you as well. So AI, specifically, how could it benefit your day to day outcome? How how could you work better with the product if we put a little bit more intelligence into the solution? The second is around integrations. We've definitely had a few requests where customers would like us to look at integrating with cluster seven or with legal hold. So they're already on our radar, but is there any other Mitratech products you'd like us to integrate into? And the final one is probably a plea to actually what was else would you like us to tackle? What other topics are important to you that you would like us to look at? Just gonna talk to you a little bit about how product management works within Mitratech as well. So this slide shows how customer feedback directly shapes what we build. It's a methodology we've used to to deliver improvements to the platform. We gather ideas continuously through customer success, user interviews, support cases, and surveys. We're prioritizing using the voice of the customer, scoring and ranking inputs to balance customer impact with deliverable feasibility. We deliver through high quality predictable releases with testing, clear communications, and training to drive adoption. The goal isn't just to ship features. It's to make sure that customers are confident and successful using them. And you'll be pleased to know I am very quickly wrapping up. Okay. So customer working group gives customers direct voice in how data store evolves, a focused forum for discussing real use cases, validating requirements, and ensuring that what we're building matters the most. All customers are invited, though individual sessions will be scoped to specific topics to keep the discussions focused. Broader feedback will continue flowing through the customer portal. If you're not aware of that, I will send out a communication on that shortly. Our approach is iterative. We start with a minimal valuable minimal minimal put my teeth in. Minimal viable product, and then we evolve from that based on customer feedback and input. Joining customer work group doesn't guarantee that it's immediate delivery, but it will help shape and prioritize our our future. The the ask is like roughly one hour every three weeks join an active design stage. Okay. So Do you want to say. this one? Yeah. Go on. Well, now before we get on to that, I just think, I just wanna stress, you know, what Wayne is saying. Like, look, we don't like to develop things in isolation. The survey that Wayne sent out, I I I'm I'm sorry. Most most importantly, apologies for a couple of the slides. There were some nice grids in there with, which did not result themselves very well, through the platform. So we will make sure that each of you get the slides. So, a lot of what Wayne was talking about will make sense and apologies for the few people where some of their browsers weren't working correctly during the demo. But again, this is all recorded so you'll get that back. You'll be able to catch up on that. But I think, yeah, the most important thing here is, you know, we are looking for your feedback. This group of people from Rande store are, generally not shy in giving us feedback and ideas. So please, please continue that. But as we go on that journey of putting, AI into datastore and enabling AI and datastore, we do want your ideas, so that we can find the common, pain points and common opportunities so that we can, we can resolve that. I will keep talking, but please do ask any questions. I know there's been, one one or two in. Just on Interact. So, some of you are familiar, Interact is our annual conference. We're very keen in getting people together. It's in, Phoenix this year in October. It's a great opportunity to meet peers, to get, to meet, product people, say, other clients and understand how they're leveraging both Datastore and other, other products, that Mitratech comes to, has to offer. It's quite a nice setting as well, so it would be great, to see some of you there. And it's a great great opportunity. I don't know, Wayne, what if there's anything else you had after this. Nope. It was open for sort of questions at that point. Yeah. So if there are any questions at all, from anybody, I think, so Phil's answered the, web version stateless or stateful. That's stateless with some caveats. Is there any other questions? Please put them in the q q and a. If not, thank you everybody for joining. Again, apologies for some of the technical difficulties you had and apologies for the resolution of some of the slides. They will be distributed to you. Risen, please do not be shy in answering, the survey Wayne's sent out. And then, as he said, we are, keen to convene those customer working groups with you all, to get your feedback and to help shape the product, moving forward. But thank you very much for your time. Thank you, Wayne and Phil, for running the