Purpose. This memorandum documents that the Lume continuous microbial water quality sensor derives from, extends and completes work performed under prior Small Business Innovation Research funding agreements, and is therefore eligible for award as an SBIR Phase III under 15 U.S.C. 638(r). It is written so a contracting officer can place it in the file in support of a sole-source award.
SweetSense Inc, doing business as Virridy, Boulder, Colorado. UEI M9YULLTP4PH8. CAGE code: to be filled. Small business concern. SweetSense Inc is the awardee of record on the SBIR funding agreements cited below and is the entity that developed the technology.
| Award | Program | Period | Amount | Principal investigator |
|---|---|---|---|---|
| NSF 1621444, Predictive Algorithms for Water Point Failure | SBIR Phase I | 1 Jul 2016 to 31 Jul 2017 | $224,562 | Evan Thomas |
| NSF 1738321, Predictive Algorithms for Water Point Failure | SBIR Phase II | 1 Sep 2017 to 31 Oct 2021 | $1,313,725 | Evan Thomas |
| NASA 80NSSC18P1957, Nanophotonic Capillary Distiller | SBIR Phase I | 24 Jul 2018 to 31 Dec 2018 | $124,565 | Evan Thomas |
The NSF awards were made under the National Science Foundation SBIR program and the NASA award under the NASA SBIR program. All three were made to SweetSense Inc.
The company also holds two NSF Convergence Accelerator awards, the larger of which runs into 2027:
| Award | Program | Period | Amount | Principal investigator |
|---|---|---|---|---|
| NSF 49100425C0009, Convergence Accelerator Future Water Systems | NSF Convergence Accelerator | 5 Jun 2025 to 17 Jul 2027 | $3,598,706 | Evan Thomas |
| NSF 49100424C0011, Convergence Accelerator Track K: Equitable Water Solutions | NSF Convergence Accelerator | 22 Jan 2024 to 21 Jan 2025 | $649,770 | Evan Thomas |
These are not SBIR or STTR awards and are not relied upon for Phase III eligibility. They are stated here because they show active federal investment in the same water monitoring line of work, currently under contract.
The Phase I award developed "predicative machine learning algorithms for water point failures derived from cellular reporting electronic sensors installed on rural water infrastructure," using "an ensemble of robust machine learning classification techniques, using cross-validation methods to tune model parameters and evaluate performance, in order to develop a data-adaptive system."
The Phase II award states its objective as to "develop and apply machine learning statistical tools to Internet of Things (IoT) water delivery and water quality sensors." Its technical approach was to "develop universal, solar powered cellular and satellite IOT hardware for each service type," and to address site-to-site variability "through cloud-based sensor fusion and statistical learning," rather than through bespoke engineering at each installation. Phase I had demonstrated "the application of simple sensors and sophisticated machine learning to identify off-nominal service delivery" and "solving the problem of heterogeneous customer hardware with a homogeneous sensor platform and adaptive machine learning backend."
The NASA award applied the company's sensing and water systems work to water recovery hardware for spaceflight and terrestrial use. Its stated problem was that "the current generation of spacecraft and terrestrial water recovery technologies are often prone to failures caused by biofouling and mineral scaling, which can clog mechanical systems and degrade the performance of capillary-based technologies." It establishes a second federal agency SBIR relationship in water systems. The derivation of Lume set out in section 4 rests on the NSF awards.
Three elements were established under these agreements: low-cost universal sensor hardware operating unattended in power-constrained field conditions, cellular and satellite telemetry from that hardware to a cloud service, and statistical learning applied to the resulting data to produce a decision-relevant water service indicator. Water quality was named explicitly in the NSF Phase II objective.
Lume is an in-water optical sensor that reports continuously over cellular telemetry and estimates microbial contamination, specifically E. coli, from optical measurements. It measures tryptophan-like fluorescence, turbidity and water temperature, and applies a fitted statistical model to those measurements to produce a quantitative water quality estimate.
The derivation is direct and runs through each of the three elements above:
The company's SBIR Company Commercialization Report, filed with the Small Business Administration, records three issued patents as resulting from these SBIR awards:
The first of these covers the fluorimetry method Lume applies to detect organic and microbial contamination, and the second covers the machine learning applied to the resulting water data. Together they are the patented form of the work the SBIR awards funded, and they read directly onto the sensor offered here.
Four further applications are pending, of which the first covers the sensor package offered here:
The three PCT applications are pending in the United States, Europe, Canada, Australia, India, China, Brazil, Mexico, South Korea, Norway and Japan.
Evan Thomas was the principal investigator on each of the awards cited above and directs this work today as the company's chief executive. The people who performed the SBIR work are the people offering the sensor.
Lume is in commercial service with United States municipalities and water utilities, and is under evaluation by the Air Force Research Laboratory.
15 U.S.C. 638(r)(1): "In the case of a small business concern that is awarded a funding agreement for Phase II of an SBIR or STTR program, a Federal agency may enter into a Phase III agreement with that business concern for additional work to be performed during or after the Phase II period."
15 U.S.C. 638(r)(4): agencies shall, to the greatest extent practicable, "issue, without further justification, Phase III awards relating to technology, including sole source awards, to the SBIR and STTR award recipients that developed the technology."
15 U.S.C. 638(e)(4)(C) defines Phase III to include "work that derives from, extends, or completes efforts made under prior funding agreements."
SBA SBIR/STTR Policy Directive section 4(c)(3) provides that the competitions held for Phase I and Phase II satisfy the competition requirements of the Competition in Contracting Act, and that "it is sufficient to state for purposes of a Justification and Approval, if one is deemed required by the agency, that the project is an SBIR/STTR Phase III award that is derived from, extends, or completes efforts made under prior SBIR/STTR Funding Agreements and is authorized pursuant to 15 U.S.C. 638(r)(4). Further justification is not needed."
Three further points bear on the award:
A Phase III award is an SBIR award and carries SBIR data rights. Under DFARS 252.227-7018, as revised effective 17 January 2025, those rights are protected for 20 years, after which the government holds non-expiring government purpose rights. A contracting officer may not require relinquishment of SBIR data rights as a condition of award.
Award a Phase III contract to SweetSense Inc for quantity Lume sensors and associated data service, sole source under 15 U.S.C. 638(r)(4), funded with appropriation appropriation.
Company point of contact: Evan Thomas, Chief Executive Officer, SweetSense Inc.
This memorandum states the company's documentation of SBIR derivation for the contract file. The determination that the work qualifies as Phase III rests with the awarding agency.