Think of ImplicitSearch™ as being like an AI Bloodhound with you as its handler.
You instantly train patent-pending ImplicitSearch™ on the scent of content. ImplicitSearch™ then seeks out content having a similar scent.
You instantly improve its hunting abilities by selecting results you like the most and retraining & honing it ... on the fly.
Now that's one smart puppy!
A pristine ImplicitSearch™ engine is instantiated for each personalized search session.
Like others, we allow you to enter keywords or Boolean strings.
Unlike others, we allow you to "seed" your search sessions with exemplary reference data.
This tells the patent-pending ImplicitSearch™ AI to "Go find more like these".
With portable search sessions, experts can seed a session for others to complete on their behalf.
ImplicitSearch™ not only learns on the fly by the reference data used to "seed" your search session, it also learns while you use it.
See a search result you like? Check the box next to it, then re-click the ImplicitSearch™ button.
This is essentially you telling the AI Bloodhound "Good girl! I like these results...now go find me MORE like them!"
Our patent-pending, instantaneously-trainable AI involves several breakthroughs in personalized ML search.
ImplicitSearch™'s ability to find something "like" something means it can be used to classify content via its implicitness - whether that content is at rest or in motion.
1) Train a dedicated ImplicitSearch™ engine on documents or content having a known classification (or content that you just want to "clusterize" so that it's all right there at your fingertips)
2) Deploy that engine in line with RPA or other content capture mechanisms. Content that's implicitly similar to that which the engine was trained on will be given a high AI score
3) Use the AI score from that engine to apply a classification or other kind of metadata tag to that content. Route content at / above an AI score threshold to individuals, teams, or systems who want or need that content
WeR.ai enables the patent-pending ImplicitSearch™ experience in *your* interfaces via API calls or batch processes under a "White Label" agreement. We maintain the AI architecture and keep your use case working to spec as subscription AI as a service.
Content aggregators differentiated their experiences by allowing customers to find quality results faster because they can select a result they like then tell the AI to go "Find more like this"?
Staffing companies attracted more candidates because they offered AI powered services that matched people to roles at the resume level? (And saved money via operational efficiencies while doing so)?
Professional services firms used ImplicitSearch™ to deliver higher quality "audit" type engagements involving finding, "clusterizing", and classifying unstructured content? And delivering on more of these types of engagements because each delivery team requires fewer and fewer resources thanks to the AI?
Attorneys used ImplicitSearch™ for e-Discovery? Find something of relevance - check the box next to it - click the ImplicitSearch™ button - find instances of content that are implicitly similar...
Insurance claim analysts "clusterize" implicitly similar claims to streamline adjudication processes?
This list could go on and on...
ImplicitSearch™ has been tuned on the Medical Literature content domain. This allows life sciences companies (like Pharma, BioTech, Med Devices) to more quickly find the peer-reviewed medical publications containing clinical evidence needed for product performance and regulatory compliance purposes.
ImplicitSearch™ has been tuned to a particular type of legislative content so that this content can be detected in not only bills that were passed into law, but also in legislation that is still in draft mode. This gives this company greater insights into what's coming down the legislative pike and - as a natural follow-on use case powered by NLP and NLU - what the implications of this law appear to be.
ImplicitSearch™ is being deployed in a Capture -> Classify -> Route mechanism to help streamline the activities of teams of highly-trained experts. Our patent-pending technology is able to detect the unstructured content "signal" from the torrential, captured content "noise". This can provide both a better user experience and enable greater productivity.
ImplicitSearch™ is being deployed in a staffing use case that allows recruiters to more quickly find the right candidates for open positions via AI scoring on resumes. And this use case can be easily inverted (Maverick, is that you?) allowing candidates to upload a resume and be told which positions appear to be the best fit for them.