MAVEN CAPITOL CONSULTING, LLC
We provide expert political consulting powered by advanced economic analysis, giving you clear, actionable visibility into the political factors that impact your campaign.
Our Core Mission: Ensure you stay fully informed of the political landscape so your campaign is never caught off guard.
Companies pour resources into lobbying firms in order to track bills that affect their business — and bills still slip through, sometimes because a targeted provision was quietly written into a bill whose title has nothing to do with it. Maven Ultra is our own bill-tracking algorithm: it watches the Maryland General Assembly continuously, reads every bill in full, and even listens to what is said at hearings, so nothing relevant reaches the Governor's desk without our clients hearing about it first.
Pulls Maryland's official legislative dataset on the same cadence the state itself updates it — hourly during session — covering every bill from pre-filing through introduction, committee action, engrossment, and enrollment. Full bill text and committee hearing testimony are pulled alongside it, not just the title and summary.
Every bill, every action it takes, and every hearing document tied to it is kept in a structured, queryable history, so we can show a client not just where a bill stands today but everything that led there.
Each bill is sorted by topic — liquor licensing, energy, education, taxation, health care, and more — based on its full text, not just its title or synopsis. That catches the kind of provision skimming headlines would miss: legislation quietly touching a client's interest through a bill that reads like it's about something else entirely.
Using the bill's own language plus testimony from expert witnesses and practitioners at its committee hearing, Maven Ultra scores where a bill sits on a −1 (opposed) to +1 (supportive) scale for each topic it touches — a proprietary model trained specifically on legislative language, not a generic off-the-shelf sentiment tool.
The moment a bill on a client's topics of interest is introduced, advances, or turns out to touch their interest through a hidden rider, Maven Ultra pings them — before it's news, and long before it's law.
A generic tracker can tell a client a bill exists. These three capabilities are what turn that into intelligence a client can actually act on.
Every client tells Maven Ultra what matters to their business during onboarding — where they operate, what they're licensed to do, what they spend on, what could hurt their reputation. Every relevant bill is then scored 0–100 against that specific profile, not a generic topic label, with the exact matched language shown as evidence.
A topic's mood isn't static. Maven Ultra tracks how sentiment on a topic shifts session over session, so a client can see momentum building or opposition hardening — not just a single all-time average.
Beyond scoring whether testimony reads for or against a bill, Maven Ultra tracks which specific arguments are being made, and flags when the same argument resurfaces in a different bill's hearing later — an early read on which ideas are actually gaining traction in Annapolis.
Bubble size reflects the number of bills Maven Ultra categorized under each topic. Hover to view topic labels.
Illustrative example: built from a representative sample of Maryland's 2026 Regular Session, run through Maven Ultra's proprietary topic engine. Subscribers see this same view refreshed continuously, for the complete session, on the same cadence the state itself publishes new data.
The same bills, scored for one example client's actual business — not a generic topic match. Hover a bar for the specific evidence behind the score.
Illustrative example: real Maryland bills scored against one sample client profile (a liquor retailer holding a Class A license) using Maven Ultra's proprietary exposure model. A subscriber's own score reflects their own onboarding profile — the same bill scores differently for every client.
Beyond counting bills, Maven Ultra reads them: each topic is scored from −1 (opposed) to +1 (supportive) using the bill's own language plus what was said at its hearing. Hover a bar for the underlying bill count.
Illustrative example, not a statistical finding: scored from a small sample of real Maryland bills and their committee hearing testimony, sourced from the Maryland General Assembly's own public records. Subscribers get full-session coverage that deepens as our models continuously retrain on new hearing testimony throughout the session.
The same topics, tracked session over session rather than flattened into one number. Hover a point for the bill count behind it.
Illustrative example: the same real bills behind the chart above, split by session instead of averaged across all of them. Several points reflect just one or two bills at this sample size — a subscriber's own trajectory sharpens as coverage accumulates session over session.
Maven Ultra doesn't stop at scoring tone — it tracks the specific arguments being made, and flags when one resurfaces in a different bill's hearing.
Illustrative example: a real argument, found verbatim in real Maryland committee testimony submitted on two different bills, sessions apart. Subscribers see this run continuously across every hearing Maven Ultra tracks, not just the topics shown here.