SBIR-STTR Award

Pushing the Boundaries of Intelligent Assistants for Financial Services
Award last edited on: 1/16/2019

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$975,000
Award Phase
2
Solicitation Topic Code
IT
Principal Investigator
Michael Laurenzano

Company Information

Clinc Inc (AKA: Clarity Lab)

205 East Washington Street Suite D 3rd Floor
Ann Arbor, MI 48104
   (858) 205-3027
   clinc@clinc.com
   www.clinc.com
Location: Single
Congr. District: 12
County: Washtenaw

Phase I

Contract Number: ----------
Start Date: ----    Completed: ----
Phase I year
2016
Phase I Amount
$225,000
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will arise from the development and release of the world's first open source Intelligent Virtual Assistant (IVA) platform. The platform will be made available to the world as open source software free of charge, and will be surrounded by a set of commercial offerings that include the deployment and customization of the software as well as software-as-a-service (SaaS) offerings that will allow users of the platform to painlessly create and deploy IVAs. Beyond the commercial applications of IVA technology, the open source release of the platform will help foster a healthy, active open source community around the IVA technology, allowing it to be leveraged as a machine learning research platform and accelerating IVA adoption in important non-commercial settings such as non-profit education and improving technological access for the disabled. This Small Business Innovation Research (SBIR) Phase I project will address the significant computer systems challenges involved in seamlessly orchestrating the massive amounts of computation among complex pipelines of algorithmic components required to power intelligent virtual assistant (IVA) technologies. The computation required to power IVAs is large enough that such software systems will likely run in large datacenter infrastructures comprised of complex ecosystems of different server types and accelerator platforms. This project will address these challenges by building a centralized software mechanism within the IVA platform for monitoring job execution to facilitate efficiently mapping sub-tasks within the IVA computation to the available hardware resources in the datacenter.

Phase II

Contract Number: ----------
Start Date: ----    Completed: ----
Phase II year
2017
Phase II Amount
$750,000
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is in providing state-of-the-art tools allowing anyone to build and deploy domain specific commercial intelligent virtual assistant (IVA) solutions. These tools allow others to understand how IVAs should be architected and integrate IVA technology into their offerings. IVAs have shown promise in numerous commercial domains including financial services, healthcare, education, law enforcement, and retail, to name a few, reducing the barrier to knowledge access within domains by providing a medium for people to converse naturally with sophisticated computer and information systems.This Small Business Innovation Research (SBIR) Phase II project will address the significant technological challenges involved when scaling the domains and capabilities of an Intelligent Virtual Assistant (IVA). This project will innovate in designing scalable artificial intelligence models capable of learning and identifying hundreds or thousands of learned concepts, and designing the accompanying system architecture to support the growing compute demand of sophisticated algorithms. Specifically, the project aims at achieving: (1) Scalable Intelligence: the ability to handle hundreds or thousands of competencies and extractable semantic concepts, allowing users to interact with the system with unbounded, unconstrained language; (2) Customizable Intelligence: the ability to allow customers to (semi-) automatically train and (re)train and customize the intelligence on demand (adding new competencies, identifying new slot-value pairs, modify responses); (3) Conversational Complexity: support multi-turn conversations, where the context from prior utterances is used to refine and understand what the end-user is trying to accomplish; and (4) Scalable System Infrastructure: enhance open source IVA software infrastructure to seamlessly scale up and down the computational resources allocated for each intelligence engine based on load.