AI for Colorado water rights firms. More matters with the team you have.
AI can watch the monthly water court resumes, pull decree and diversion records from public state data, and search a firm's own past reports in minutes. Modern Thesis helps owners of Colorado water rights engineering firms and consultancies put that to work, so the team can take on more matters without hiring engineers who are hard to find.
At a glance
- Who it's for: owners and principals of Colorado water rights engineering firms and water consultancies, usually with no CTO, at companies with $10M+ in annual revenue.
- What Modern Thesis does: AI strategy, change management, implementation and ongoing stewardship, from one team.
- How it starts: a strategic assessment that measures how the work moves today and ranks where AI pays first. See the assessment.
- Where: based in the Denver area, with an office at 11001 W 120th Ave, Ste 400, Broomfield, CO 80021. On site along the Front Range and remote.
- What it doesn't do: give legal advice, stamp engineering work, or publish a rate card. Each engagement is priced to its scope after a first conversation.
Who is this page for?
This page is for the people who run a Colorado water rights engineering firm or water consultancy and are being asked what the firm is doing about AI. Often a few engineers already use ChatGPT on their own, leadership wants it organized and private, and the backlog keeps growing while the hiring market stays thin. The ACEC Research Institute's Q2 2026 survey found 84 percent of engineering firms still have at least one open position.4 If that sounds like your firm, the question worth asking is where AI adds capacity to the work you already bill.
Where does AI help in Colorado water rights work?
AI helps most where water rights work is repetitive, record-heavy and deadline-driven. Colorado has seven water divisions, and each water clerk publishes a monthly resume summarizing every new application.1 Statements of opposition are generally due by the last day of the second month after the month an application was filed,2 so missing a filing that touches a client's rights is expensive. The state's HydroBase database holds the structures, decreed rights and decades of diversion records that engineers check on almost every matter.3
These are examples of what can be built, not past results:
- Read each division's monthly resume and flag the applications that name a client's structures, stream reach or water district, with the opposition deadline attached.
- Pull a structure's decreed rights and diversion history from public state data, with data-quality gaps marked, as a first pass before an engineer's review.
- Search the firm's own past reports, engineering analyses and correspondence in plain language, with every answer linked to its source document.
- Check augmentation plan accounting spreadsheets for missing entries, unit mismatches and numbers that break from the prior period.
- Keep a filing and deadline calendar that updates itself when a new resume or court order comes in.
What does Modern Thesis do for a water rights firm?
Modern Thesis covers four disciplines with one team, so the firm isn't stitching together a strategist, a developer and a trainer. In strategy, Jim Coleman and the team map how resumes, research, accounting and reports move through the firm today. In people, we line up incentives and train the engineers and staff who will use the system (a system nobody uses returns nothing). In implementation, our AI specialists and Forward Deployed Engineers build the workflows and connect them to the tools you already run. In stewardship, we stay to monitor accuracy, keep the system current as AI models change, and report the return against the baseline.
How does an engagement start?
Every engagement starts with a strategic assessment. We learn how the work really gets done, measure the baseline on the workflows that matter (time per matter, rework, missed or late items), and rank the opportunities by return. It is the first step of the build, so it ends with the first system defined. If AI won't pay for itself somewhere in your firm, we'll tell you. Our guide to measuring AI ROI explains the baseline method in more detail.
What does this look like on real Colorado data?
We built the Water Right Snapshot, a working demo on public Colorado Division of Water Resources data. Enter a WDID or search a structure by name within a water district, and in about a minute it returns the structure, its decreed rights, its diversion records with data-quality flags, and nearby wells and gauges. It is a first pass, and it doesn't replace an engineer's review. It shows the kind of tool a firm can have on its own records and workflows.
Does AI replace licensed judgment?
No. AI supports the work, and a licensed engineer stays in charge of every stamped number. Engineering firms rightly worry about professional liability when software touches their work, so the systems we build show their sources, keep a person at every decision that matters, and log what the AI did. That makes the engineer's review faster, which is where the capacity comes from.
When is something else the better choice?
Sometimes an outside team is the wrong answer, and we would rather say so. If one purpose-built water rights tool covers what you need, buy it and train your team on it. If the main goal is better writing and email, the ChatGPT or Copilot licenses you already pay for may be enough (our comparison of Copilot or ChatGPT and an AI partner walks through the difference). An outside team earns its cost when the work crosses several systems, needs to be accurate enough to rely on, and has to keep working after the people who built it move on.
How Modern Thesis handles this
We put AI to work inside xFusion, the 70-person company Jim co-founded, and then for several of its clients. We bring that same operator approach to water rights firms: start with the assessment, build what pays first, and stay to keep it running and measured. Ongoing stewardship has no set end date, and your firm owns its data, accounts, code and documentation throughout.
Questions
Can AI help a Colorado water rights firm without risking client confidentiality?
Yes, if the system is set up for it from the start. Public records like the water court resumes and HydroBase carry no confidentiality risk. A firm's own reports and client files are different, so they should sit in a private system that only your staff can search, with access agreed in writing. Modern Thesis never uses client data to train AI models, ours or anyone else's, and the client owns its data, accounts and code.
Does AI replace the water engineer's judgment?
No. AI is good at finding, sorting and drafting: pulling every decree on a structure, flagging resume entries near a client's rights, or assembling a first draft of a records summary. The engineering opinion stays with a licensed engineer, who reviews the output and signs the work. A well-built system shows its sources so that review is fast, and it keeps a person in charge of every number that goes into a report or a filing.
We already use ChatGPT or Copilot. Is that enough?
Keep them. General assistants are useful for writing and quick questions, and many engineers already get value from them. What they don't do on their own is connect to the state's water data, read every new resume each month, or search your firm's archive with sources attached. Those jobs need a system built around your work and your records, and that is the part Modern Thesis builds and maintains.
There is already software for water rights research. Why would we need a firm?
Sometimes you don't. Purpose-built water rights tools now exist for resume alerts and decree search, and if one fits how your team works, it may be the right answer. A firm makes sense when the work runs across several systems: your own archive, your accounting spreadsheets, your project tracking and the public data. The assessment will tell you which path pays, including when the answer is to buy an off-the-shelf tool.
How does a Modern Thesis engagement with a water rights firm start?
It starts with a strategic assessment. We map how your team handles resumes, records research, accounting and reporting today, measure the time and error rates on the workflows that matter most, and rank the opportunities by return. The assessment ends with the first build defined. If AI won't pay for itself somewhere in your firm, we'll tell you.