Program Analysis Product
Research program offices
Program analysis sites: evidence you can audit
Per-program analytical sites where every quantitative claim links to a reproducible source and a stated confidence level.
See the engagementThe map of science,
from the people who worked out how to draw it.
Kevin Boyack and Dick Klavans have spent three decades learning to map research from the way papers cite each other. Their topic model is built into Elsevier's SciVal. At Syntheos we rebuild the map from 1.7 billion citation links and use it on the question in front of you, whether you're choosing what to fund or watching where a field is heading.
We work for research funders, foundations, medical schools, and defense and policy offices. Clients include DARPA, the Andrew W. Marshall Foundation, and Georgetown.
The map, checked against what happened
Our 2018 map, checked against 2024.
We took the map as it stood at the end of 2018 and flagged the fields it showed gaining ground, the ones growing fastest and drawing citations from more of science each year. Then we looked at where those fields were six years later.
Of the 1,830 fields it flagged, 514 broke out, outgrowing nine in ten of their peers. That's more than one in four, nearly three times the rate across all fields. The lower a field scored in 2018, the less likely it was to break out.
mRNA vaccines were on the 2018 list. That community held Katalin Karikó's 2005 paper on modified RNA, which won the Nobel Prize in 2023, and its output grew sevenfold by 2024.
We wrote the rules of the test down before we looked.
Share of fields that broke out by 2024
0%
10%
20%
30%
Base rate, 10%
3%
28%
Lowest 2018 signalHighest tenth, flagged
| Tenth of 2018 signal | Broke out by 2024 |
|---|---|
| 1 | 3% |
| 2 | 4.9% |
| 3 | 5% |
| 4 | 5.8% |
| 5 | 6.8% |
| 6 | 7.8% |
| 7 | 9.6% |
| 8 | 11.7% |
| 9 | 17.3% |
| 10 | 28.1% |
A portfolio on the map
One investment that would lift six awards at once.
We took ARPA-E's public record of 113 awards and the 899 papers they acknowledge, and placed every paper on the map. The awards spread across 307 research communities. Fewer than one pair in a hundred shares any ground at all.
The ground they share most is a method, machine learning for materials discovery. Six awards working on batteries, superconductors, alloys and hydrogen all publish there. A breakthrough in that one community would lift all six. That makes it a strong candidate for the next dollar, and no program chart would point you there.
Machine learning for materials discovery
- Lithium-metal batteries
- Nickelate superconductors
- High-entropy alloys
- Alloy thermodynamics
- Hydrogen electrolysis
- Packing optimization
Where your portfolio's knowledge comes from.
We traced every paper ARPA-E's awards cite back to where it was written. Chinese institutions produce 31 percent of that research, against 19 percent of the world's output.
In lithium-metal batteries, which 28 awards draw on, Chinese institutions write 62 percent of the papers and American ones write 12. Reading that work is good science. The question is where capacity at home is thin enough to matter, and the map answers it before a supply shock does.
Chinese institutionsUS institutions
Hydrogen evolution catalysts · 21 awards draw on it
67%3%Lithium-metal batteries · 28 awards draw on it
62%12%CO₂ reduction to fuels · 33 awards draw on it
52%9%Machine learning for materials · 32 awards draw on it
24%29%
Every portfolio has places like these. Some are deliberate and some nobody planned. Send us yours and we'll show you which is which.
Map your portfolioThe map
Every finding on this site happened somewhere on this map.
Each dot is one of 102,903 research communities, placed by how their papers cite each other. Fields that read each other sit close together.
Loading the map
Each dot is a research community, colored by discipline.
Click any community to open its full profile in the explorer.
0.0BCitation Links Mapped
The citation record under the Map of Science. We follow every link between papers in the global scientific literature to find its research communities.
0+Audited Claims
Every number we deliver, in a report or in a live tool, links to the source query that produced it and reruns on demand. Auditors can pull any number at random. Regulators can verify the math without our help.
0+Peer-Reviewed Publications
Authored by the Syntheos team across science mapping, AI policy, computer security and privacy, and research security, including work in top-tier venues like Nature, PNAS, USENIX Security, ICLR, FAccT, and Quantitative Science Studies.
0Black Boxes
Every output traces to source evidence through W3C PROV lineage. No opaque models. No silent fallbacks.
Trusted by leaders in defense, healthcare, research, and public policy
Work
Selected work.
Engagements end in whatever the decision needs, from a briefing to a system the client runs for years. Each of the four below solved a different shape of problem.
Decision Platform
Andrew W. Marshall Foundation
Deepfield: a modular assessment platform
An eleven-stage strategic assessment pipeline that turns a query into a defensible course of action with full evidence lineage.
See the engagement
Human-AI Teaming System
Georgetown School of Foreign Service (SEST)
Georgetown Wicked Problems Lab: a classroom where AI assists but never decides
A teaming platform in classroom use at Georgetown. The AI listens quietly and helps on request, while phase gates, peer review, and a twelve-rule delegation contract keep every real judgment in student hands.
See the engagement
Research Intelligence Tool
University of Michigan
Pathfinder: research pathway navigation for a map of science
A research pathway explorer that lets users chart and narrate routes between research communities on a global map of science.
See the engagementGovernment & DefenseBuilt for federal
Built for federal
acquisition.
Assessments and decision tools built to survive Congressional oversight and meet the standards the DoD AI office is setting.
View Defense CapabilitiesSAM.gov RegisteredNIST 800-171 In ProgressDFARS 7012 In ProgressResponsible AI by Design
Past Performance
DARPA, CSET, Marshall Foundation, Noble Reach
Mission Areas
Competitive Assessment, Technology Scouting, Decision Architectures
Acquisition Vehicles Performed
Direct Award, OTAs, BAAs
What we do
Answers in the form
the decision needs.
Every engagement begins with a decision someone has to make and stand behind, in a field too large to read unaided. Most end in a briefing or a written assessment. When a question keeps coming back, we build the tool that keeps answering it, and the last four below are tools we built that way.
01
Briefings and Assessments
Most engagements end here. A briefing on a research field, a portfolio review, or an assessment of an emerging technology, delivered to the people deciding and written to hold up when someone asks how you know. Built on the Map of Science and read by people who've worked in the field.
Proof: the 2026 Watch List
- Briefings on a research field and who leads it
- Portfolio maps showing overlap, dependence and open ground
- Emerging technology and research security assessments
- Prospective assessments written before results arrive
02
Program Analysis
What a program's work did once it left the program office, who picked it up and where it went. Delivered as an assessment, or as a live site that keeps the picture current. Every number carries a reproducible query and a confidence level.
Proof: research program offices
- Downstream uptake, diffusion and commercial translation
- Structured evidence ledger behind every claim
- A reproducible query behind every number
- An optional live site that refreshes as new papers arrive
03
Strategic Assessment Tools
An eleven-stage assessment pipeline you run yourself. Every stage carries W3C PROV lineage, so any final recommendation traces back through the whole chain to the source evidence. Built for standing strategic-assessment and competitive-intelligence work.
Proof: Deepfield
- Modular pipeline, eleven stages, tuned to your domain
- Knowledge graph, ACH-based reasoning, wargaming
- Your analysts run their own assessments with it
- Full evidence lineage on every recommendation
04
Research Intelligence Tools
Research consoles over specialist corpora. A researcher asks a question and gets an answer cited to the page, with figures that separate what the sources say from what the model inferred. We build a knowledge graph over the corpus when the questions need one. Built for institutions that want researchers to think with a corpus as well as read it.
Proof: Andrew W. Marshall Foundation
- Answers cited to document and page
- Hybrid vector and full-text retrieval, reranked
- Cited versus inferred marking in every figure
- A knowledge graph where the corpus calls for one
05
Human-AI Teaming Systems
Orchestrated AI assistance with human judgment in the loop. A delegation contract constrains what the AI is allowed to do, and database-level phase gates enforce it. Built for learning environments and decision-critical work where the AI must help but never decide.
Proof: Georgetown SEST
- Agent orchestration across fast, deep, and QA tiers
- Delegation contract constraining AI authority
- Database-enforced phase gates
- Voice and text surfaces, instructor tooling
The form follows the decision. The evidence trail behind it is the same in every engagement.
Where to start
Start with
two weeks.
Send us one decision and the material behind it. We run our methods on it and walk you through the result. There's no fee.
By the end of the walkthrough you'll know whether we showed you something you couldn't see before, and we'll give you a fixed price for the full engagement.
Send us a decisionYou sendIn two weeks you get
A research area or a portfolio
A map of the research communities it touches, and where the open ground is.
Read the business caseAn emerging technology you have to decide on
A briefing on where the field is heading, who leads it, and what it depends on.
Read the business caseA program name or a BAA
An assessment of what the program's work did once it left the program office.
Read the business caseOne strategic question
A first-pass assessment with the evidence and the assumptions laid out.
Read the business caseFifty documents from your corpus
Answers to your questions about them, cited to the page.
Read the business caseWe take one on when the decision is consequential, the structure behind it is hard to see, and the person who owns it will be in the room for the walkthrough.
Who we work for
Where decisions
don't tolerate hand-waving.
These are the people who own the decisions we work on, in the domains the team came up through. The question changes from one to the next. The job stays the same. We show where to act and make sure the choice survives scrutiny.
Federal R&D Funders & Program Offices
Which programs to start and which to end. The portfolio then has to be defended to Congress, the press, and the next administration. We bring quantitative portfolio analysis, science mapping, growth-trajectory forecasting, and AI-assisted research-opportunity discovery to the call before it's made and to the audit that follows.
Explore capabilitiesFoundations & Strategic Philanthropy
Where a single grant will move a research community, and where it will vanish. Foundations make that call over long horizons, and the decision has to outlast the staff who made it. We've mapped funding portfolios across decades, modeled where a grant moves a field, and built research tools over specialist archives.
Explore capabilitiesMedical Schools & Biomedical Funders
Which lines of translational research to back, and what the clinical evidence supports. We do translational research forecasting, research-funding portfolio analysis, and clinical-evidence synthesis for medical schools, biomedical agencies, and clinical specialty boards. It's built on years of running a research-intelligence operation inside an academic medical center.
Explore capabilitiesAI & Emerging Technology Policy Teams
Which emerging technologies deserve attention now, and where research security is exposed. We do AI research-trend analysis, research-security assessment, and long-horizon emerging-technology forecasting, informed by years of work at the institutions that set this policy. The vocabulary, the methodology, and the relationships are our own.
Explore capabilitiesDefense & National Security
Where an advantage can be built or lost over a long competition. Competitive assessment demands synthesis across military, economic, and technological domains over long time horizons. Traceable reasoning. Explicit assumptions you can challenge, test, and refine.
Explore capabilitiesOutside These Domains
The domain matters less than the shape of the decision. We ask three questions. Does the decision carry real money or mission consequence? Is the structure that should drive it hidden from the people making it? Could seeing that structure change the answer? Three yeses and we should talk.
Explore capabilitiesThe team
Small group.
Deep bench.
Syntheos is a small firm by design. Every engagement is staffed by principals — people who came here from the places where high-stakes decisions are actually made.
The Office of Naval Research. The Office of the Secretary of Defense. The MacArthur Foundation. Sandia. The Naval Research Laboratory. CSET. The University of Michigan Medical School. Between us we have decades of peer-reviewed work in science mapping, research evaluation, science policy, AI policy, computer security and privacy, and research security.
You don't get handed off to a junior team. You get the people whose names are on the papers.
“
“Every decision faces two questions: was it right, and how do you know? Everything we deliver is made for both.”
Caleb Smith
Founder & CEO
Our Approach
How an engagement runs.
01
Frame
We start with the decision, before any data. Who has to make the call, and who will press them on it? Those answers set the scope of the work and the form the answer should take.
02
Investigate
Then the analysis. We work from the Map of Science, the literature itself, your own data where it matters, and the people who know the field. What the evidence settles, we say plainly. Where it runs out, we say that too.
03
Deliver
The answer comes in the form you'll use. Often that's a briefing for the people deciding, or a written assessment they can circulate and defend. When the same question keeps coming back, we build a tool your team runs itself. Every claim traces back to its source, whatever the format.
04
Follow through
We stay close after delivery to answer the questions the work raises. Sometimes that's where it ends. More often the first answer shows a client a question they couldn't have asked before, and they bring us back to go after it.
FAQ
Questions From Leaders Who've Been Here Before
These are the questions that come up when we talk to leaders who've seen enough vendor pitches to be skeptical. They're worth asking of anyone in this space, including us.
AI projects often fail because they're framed as technical projects when they're actually organizational change projects. Someone buys a platform, a team builds models, the models perform well on test data, and then nothing changes. The decisions get made the same way they always did, by the same people, using the same inputs. The AI sits on the side, technically functional and organizationally irrelevant.
The usual culprit is starting from the wrong end. "We have all this data, what can we do with it?" is a recipe for building impressive demos that don't matter. So is "leadership wants an AI initiative." These projects optimize for what's measurable by technologists, like model accuracy, processing speed, and data coverage. Decision-makers care about whether they can trust an output, explain it to their boss, and defend it when something goes wrong. F1 scores are not on that list.
We start from the other end. A specific decision that matters, made by specific people, who answer to specific stakeholders. What evidence do they need? What does defensible look like in their world? Where does their current process break down? The technical architecture follows from those answers, not the other way around.
This is less exciting than a general-purpose AI platform. It's slower to show results in a demo. But it's the difference between a system that gets used and a system that gets abandoned.
Initiate Contact
Bring us a decision you have to make and defend.
Tell us about the decision you're trying to improve. We'll schedule a briefing with our principals to understand your environment and see whether the fit is right.
Schedule a briefing