Lumi AI nets $3.7m to unlock supply chain insights with natural language prompts, led by AgFunder

[Disclosure: AgFunderNews’ parent company AgFunder is an investor in Lumi AI.]

• Lumi AI—a startup enabling customers with out coding expertise to realize actionable insights from advanced information in firm ERP methods utilizing plain language prompts—has raised a $3.7 million seed spherical led by AgFunder.
• The spherical, which was supported by Forum Ventures, Abu Dhabi sovereign wealth fund ADQ, and strategic angel buyers, will assist the Toronto-based agency broaden its platform to help a rising roster of consumers together with a number one US grocery store chain, a prime meal-kit supplier, a number one consulting agency, the biggest retail operator within the Center East, and mid-sized CPG corporations.

Based in 2023 by Ibrahim Ashqar and Tudor Boiangiu, Lumi AI has constructed an enterprise information analytics platform with an emphasis on provide chain information enabling customers to interrogate enterprise useful resource planning (ERP) methods by way of a pure language interface.

The interface, which integrates with purchasers’ provide chain software program, operates as an clever assistant, serving to customers retrieve and interpret information, generate charts and extract tailor-made insights that beforehand would have taken days to drag collectively, says Ashqar.

“We based Lumi AI to interrupt down the boundaries between companies and their information. With this funding, we’re accelerating our mission to assist corporations democratize entry to intelligence and rework decision-making at scale.”

“Lumi AI is remodeling the way in which companies function by making analytics accessible to everybody. I haven’t seen that earlier than – such unimaginable pull in demand throughout retail, grocery, manufacturing – any trade with advanced provide chains.” Rob Leclerc PhD, managing associate, AgFunder

Eliminating information bottlenecks

Usually, if enterprise customers need to extract insights from ERP methods immediately, they’ll file a request with an in-house information workforce or somebody within the firm that may code in SQL or Python to generate a customized report, Ashqar tells AgFunderNews.

“At any time when you will have a state of affairs like that, it creates a bottleneck,” says Ashqar. “The info workforce is overloaded with requests and enterprise groups are annoyed as a result of they’re overly depending on the information workforce.”

And within the meantime, he says, “Numerous alternative stays hidden within the information and also you’re leaving cash on the desk.”

And that is the essential premise behind Lumi AI, which is “all about illumination… shedding gentle on points inside your information units,” says Ashqar, who met his cofounder Tudor Boiangiu whereas working at Deloitte’s AI follow.

“Massive language fashions got here on the scene in late 2022 they usually demonstrated an incremental capacity to code, which opened up a world of prospects. So I mocked up a proof of idea, confirmed it to Tudor, and we ended up constructing an AI information analyst providing agentic workflows for analytics, empowering folks to get probably the most from their information simply by asking questions in plain language.”

Use circumstances

Initially, Lumi AI is concentrating on corporations with provide chain information fashions that use platforms reminiscent of SAP, Oracle, or Microsoft Dynamics to run their operations, he says.

Usually these are corporations with a variety of stock information, gross sales historical past, procurement historical past, clients, distributors, payments of supplies, shipments, and so forth, he provides. “We’ve spent a variety of time on this area so we all know the information fairly nicely, so it made sense to begin right here versus saying we will do all the things for everybody.”

Within the case of a grocery store chain, for instance, he says, on-shelf-availability is a crucial metric. “So your situation is likely to be, the distribution facilities are filled with stock, so why are we seeing out of shares?”

Usually it’s as a result of some shops should not following stock protocols correctly, he claims. With a view to establish the place the issue lies, traditionally, account administration and retail ops groups must undergo dashboards, manually extract information into spreadsheets, maybe ask an analyst to usher in new information, conduct an evaluation, “and after a few week or so, they’ll conclude, ‘We have to discuss to those 5 shops.’”

With Lumi AI, he says, these groups can merely ask which shops should not following the protocols in plain language, shortly establish the offending shops, and take remedial motion.

One other key use case is figuring out discrepancies between what’s ordered and what’s shipped, he says. Massive retailers gather this type of information at a really granular degree, however there’s a lot of it, it’s “nearly unusable if you need a dashboard view,” he says. “So to see what’s happening, they need to mixture it to the next degree, which implies they lose visibility and might’t see what’s taking place on the merchandise/retailer/day degree.”

Lumi AI, nevertheless, permits customers to “drill right down to probably the most granular degree so you may see what’s really driving a dip or an anomaly or an outlier.”

Tacking ‘dashboard anarchy’

On the subject of persuading potential clients of the worth of Lumi’s providing, he says, it will depend on the maturity of the shopper. “Mid-sized purchasers usually don’t have an information workforce, or it’s actually small, so we’re giving them capacity to get insights they didn’t have entry to earlier than.”

For such purchasers, Lumi may create pre-set prompts that ask questions reminiscent of, ‘Present me gadgets the place the minimal order portions from our distributors far exceed the typical consumption for these uncooked supplies.’ This might be a great start line for negotiations with distributors which might be “making you purchase far more stock than you want, and it’s consuming up your money move,” says Ashqar.

For enterprise purchasers reminiscent of large retailers, he says, Lumi is providing a remedy for “dashboard anarchy,”  a situation characterised by “having tons of of dashboards, 95% of that are ineffective.”

As for boundaries to progress, he says, on uncommon events, potential purchasers may need a system that Lumi AI can’t hook up with. “Shopify gatekeeps its information, for instance, so Shopify clients can’t really straight question it. First you need to extract the information by way of API, migrate it to your personal information warehouse, after which you may question it. So some potential clients haven’t but acquired their information to a spot the place we will question it.”

Addressing information safety issues

Importantly, says Ashqar, corporations deploying Lumi AI shouldn’t have to fret about information safety. “From day one, we designed Lumi in a really particular method that ensures that the uncooked information is simply ever processed inside the shopper’s infrastructure. Massive enterprises love that as a result of we’re not telling them, ‘Share your information with us after which we’ll provide you with perception.’”

As for onboarding, he says, “You’ll be able to’t simply join AI to your information and anticipate magic. It wants to know the context of your information and your enterprise for it to work correctly. However we’re speaking days and weeks, not months. With the most important retailer we’re working with, we acquired them up and operating inside every week.”

Agentic workflows

Transferring ahead, he says, “We have to proceed innovating as a result of the sector is shifting so shortly.  For instance, a variety of the concepts that Tudor had on the outset had been pioneering, just like the idea of agentic workflows [whereby the AI makes decisions and takes actions autonomously based on predefined instructions and goals], a time period that didn’t exist at first of this hype, and is now nearly mainstream.”

Longer-term, he says, Lumi’s actual worth will come not simply from answering customers’ questions, however from making a system that may begin asking itself questions after which flag anomalies.

“Immediately, Lumi AI is a senior information analyst. The following evolution is it turns into an analytics supervisor that may proactively floor insights.”

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