Let’s put AI on the work you still do by hand.
We find the work AI should already be doing for you, build the system, and train your team to run it after we leave.
KZN spent two years rebuilding its own eighteen-year-old consultancy on AI. Now we do the same for research centers, government agencies, and companies. Bring two or three workflows to the first call and we will tell you which one is worth it.
Thirty minutes, no deck, and a straight answer on whether it is worth building. Or two weeks and a fixed fee if you want the answer in writing.
A typical build
8 weeks
- Week 0–2
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Scope
We map the workflow, the data, and the review process that will decide whether this can go live. You get a written brief with the scope and the fixed price.
- Week 2–6
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Build
The system gets built against your real data, in your environment, with security and records people in the room from the first week rather than the last.
- Week 6–8
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Handover
Your team is trained, the runbook is written, and the system runs without us. No retainer required to keep it alive.
Outcome: in production, owned by you
Eighteen years shipping software: research programs, state and city government, and commercial platforms built from scratch
- National Science Foundation
- DC Public Works
- State of Maryland
- Penn State
- Autodesk
- Booz Allen Hamilton
- Quorum
- Travel insurance
SOC 2 Type II · 2024
Delivered under emergency conditions, for state and city government
- 750K
- people vaccinated through the scheduling system we built for Maryland.
- 45M
- text messages sent and received for two state health departments during contact tracing.
- 1M
- vaccination appointments scheduled, at ten thousand a day when it peaked.
- 9 years
- continuous delivery for a city public works department, without a gap.
01
What we build
Whatever we build, it has to run without us.
That is the one thing the three lanes below have in common. Systems you own outright, agents that take work off your people, and two products we host and run. Different contracts, different risks, one definition of done: it is in production, it survived review, and your own team can operate it.
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Systems
Built once, yours to keep
The data spine under a department, the platform under a business, the integrations between systems that were never meant to talk. Scoped against your real data, then handed over with a runbook and a trained team. Eighteen years of these, from an enterprise service bus to a pandemic response to a commerce platform still selling today.
Federal · state · local · commercial
What we have shipped
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Agents
Work taken off people, not renamed
Expert people spending their week on data entry, chasing and reformatting: that is the pattern we look for. The agent takes that part, shows its work, and asks before anything that matters. Running today: an advisor grounded in a program’s own guidance and its funded proposals, a capability finder that cites every answer back to a source page, and the scheduled jobs that run this firm. That last one is where we learned what breaks.
Any operation where expert work turned into data entry
Agents in production
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Products
Licensed, and we run them
Software that already exists, hosted and maintained by us, so you buy a running system rather than a project. Two of them today: SimplyScholar for research centers, and a service alerting platform for city public works. Both in production for years rather than months, priced as an annual line item.
NSF centers · city departments
See both products
02
Why us
We rebuilt this firm on AI before we sold it.
There is no spreadsheet left in this company. One agent runs the operations on thirteen scheduled jobs, and each job loads its own playbook when it fires.
- A brief on what needs attention, and nothing else
- Weekdays, 9am and 1pm
- Inbox triage, where only the urgent gets through
- Every fifteen minutes
- Meeting recordings turned into commitments on the record
- Hourly
- Contracts, insurance and certificates checked for expiry
- Daily, 7am
- New federal awards read and qualified against our pipeline
- Daily, 8am
- Purchase orders and budgets checked against burn
- Daily, 9am
- Contractor invoices reconciled against logged time
- Weekly
- Utilization, time logging, and the financial summary
- Weekly
It did not start this way
The first version was thirteen separate agents, one per specialty. Every one of them decided on its own whether something was worth interrupting for, and the result was noise. One agent decides now, and the other twelve became scheduled jobs. Finding that out cost us the time it took to build thirteen agents, and it is the kind of thing you are paying us to already know.
Your security people will ask about permissions
Ours did. Contractors here get their own agent, with their own credentials, scoped to exactly what they are allowed to see and blocked from writing anything operational. That question arrives on every engagement, and we answered it for ourselves first.
Public and inspectable. The toolkit behind our India tax agent is open source under MIT, with the full cost architecture written up: what the build cost, what the first returns cost, and the architecture that got it there. Read the code and the decisions rather than take our word for it. The write-up is here.
03
Where to start
Two ways in, both fixed fee.
Most people start with one of these rather than with a build. Each is a fixed price agreed before it starts, two weeks on the clock, and a written document at the end. Neither obliges you to do anything afterwards, and neither fee is credited against a build.
You have work being done by hand
AI Workflow Review
- You bring the workflows
- Two or three pieces of work you already suspect. The month-end close, the intake queue, the annual report, the thing your best person spends Thursdays on. We do not audit your organization. We look at the work you brought.
- What you get
- Each workflow costed: what it would take to build, what it would save, what would block it, and which one to do first. Plus the ones we tell you not to automate, and why. Whoever owns the budget can read it without a translator.
- Duration
- Two weeks
- Fee
- $12,000 fixed
- Covers
- Up to three workflows
- Your time
- About six hours
- Obligation
- None
You have a pilot that has not shipped
Production Readiness Review
- What we do
- We read the code, talk to the people who built it and the people who have to approve it, and put your pilot through the review it will eventually face.
- What you get
- A written verdict of ship, fix, or stop. The specific things that will fail review, named, with what each one takes to close, and what finishing it would cost.
- The fee is not credited against a build
- A firm that credits the audit against the follow-on project has a reason to recommend the project. Ship, fix and stop are all real verdicts, and stop is the one that saves you the most.
- Duration
- Two weeks
- Fee
- $12,000 fixed
- Covers
- One pilot or system
- Your time
- About four hours
- Obligation
- None
95%
of enterprise AI pilots produce no measurable impact on the bottom line. Almost never because the model was not good enough: the demo usually works, and it is review readiness, answerability and handover that kill it afterwards.
MIT, The GenAI Divide, 2025
We reply within two business days.
04
Selected work
Systems that are still running.
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Two states through a pandemic, as prime contractor
Contact tracing, mass vaccination scheduling, community testing, and the letters people showed their employers. 45 million messages across both states, 1.5 million contact tracing cases, and around 750,000 people vaccinated through the system we built.
Maryland and Delaware
Prime contractor, 2020–2023 -
A state website that stayed up at 150,000 requests a minute
Rebuilt and hardened in four working days, ahead of a governor's press conference, because the alternative was the site falling over live on television.
State of Maryland
Four days -
A hundred million readings off a snowplow fleet, answerable in real time
Weekly reporting down to fifteen minutes, across five to seven core systems. A dozen agency systems joined into one data warehouse, GIS underneath, real-time entry from crews in the field. Ten years, four administrations and a pandemic, without a gap.
DC Department of Public Works
Continuous since July 2016 -
$120 million a year in policies, across eight countries
A travel insurance commerce platform we architected and built from nothing: eight countries on three continents, five currencies, fourteen languages, thirty-odd sites, three AWS regions. We finished in 2015. It is still selling policies today.
Travel insurance group
Subcontract, 2012–2015 -
A failing student records system, taken over and finished
Case management for a public school system, inherited mid-crisis. We got it to a first release, then led four more years of development on it. All of it under FERPA.
Public school system
Subcontract, 2010–2014 -
A capability finder that answers by handing you a person
Ask which facility can characterize a given material and get an answer built from the program’s own pages, every claim linked to its source, ending at the named manager who owns that instrument. It declines anything outside the corpus.
Federally funded multi-site
research program -
Proposal help that knows the solicitation better than the deadline allows
Grounded in the program guidance and the office's own funded proposals, so the advice is specific enough to act on at four in the afternoon. Common structured questions get an expert answer verbatim; the rest go to the model.
University research office
In production -
A department’s own data, asked in plain English
A dozen agency systems and a hundred million telemetry readings already sat in one warehouse. The chat layer turns “how many blocks did we miss on the east route last week” into a query against it, and shows the query it ran.
City public works department
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Scoring built to survive the question “how did you get that number?”
A structured self-assessment across nine dimensions, with the evidence attached to each score rather than remembered. Built so a reviewer can walk backwards from any number to the thing that justified it.
National research-impact network
05
The firm
Who actually does the work?
A senior practitioner on every engagement, start to finish. No bench, and no handoff to a delivery team you have not met. The person who scopes your work is the person who builds it, and the same person is in the room when it goes to review.
- Every engagement ends
- Every engagement has a defined end, and your team is trained and the runbook written before it arrives. A system nobody on staff can change is a system that quietly stops being used, so handover is part of the build rather than the last thing on the plan. We do not need a retainer to keep what we built alive.
- Eighteen years before the AI part
- A decade inside NSF research programs, ten years and counting with a city public works department, prime contractor on two state pandemic responses. And on the commercial side, a travel insurance platform we architected from nothing that still sells in eight countries, plus two startups: one whose product we built from scratch and took through its own SOC 2, one we advised through the growth that broke its architecture.
- We have sat on both sides of the audit
- We have been through SOC 2 Type II ourselves, and this year we took a client through their SOC 2 Type 2: the penetration testing, and the evidence responses to the auditors on operational, configuration, and vendor controls. They got their report. We have built and run HIPAA infrastructure holding live patient records for a state health department, and FERPA-covered case management for a public school system. We build everything to that bar, including for clients who have no auditor to answer to, because it is the difference between a demo and a system.
The oldest thing we built is sixteen years old.
A case management system for a public school system, built in 2010 and running under FERPA, still in service as far as we know. The one after it, a travel insurance commerce platform from 2012, is definitely still selling: eight countries, five currencies, three continents. And the oldest system we still operate ourselves is a decade-old service bus for a city department. Anyone can ship something that demos. Keeping it alive while every administration, dependency and vendor underneath it changes is a different skill, and it is the one this firm is built around.
06
Writing
What we are working on
Notes from the builds. What worked, what we got wrong, and what we would do differently.
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July 2026 · 14 min
Papa Claude and Baby Claude: put the expensive model at design time
An agent that worked on day one and would have bankrupted a filing season. The fix was an architecture, not a prompt. Open source.
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August 2026 · 9 min
The best answer a retrieval system can give is somebody’s name
Routing beats answering. Why every reply ends at the person who owns the instrument, and what that does to the definition of correct.
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August 2026 · 8 min
The chat box was two hundred lines. The warehouse took ten years
Plain English over a city department’s own data. The interface was the small part, and the integration underneath is why it works.
07
Common questions
- What happens in a Production Readiness Review?
- Two weeks. We read the code, talk to the people who built it and the people who have to approve it, and put your pilot through the review it will eventually face. You get a written verdict of ship, fix, or stop, with the blocking issues named and costed. It takes about four hours of your team's time and carries no obligation to do anything afterwards.
- How long does a build take?
- A build runs six to eight weeks from brief to a working system in your environment. Larger builds run three to six months. We do not run open-ended engagements, and we do not need a retainer to keep what we built alive.
- Can you fix an AI pilot we already started?
- Often, yes. A stalled pilot usually fails on data access, review readiness, or ownership rather than on the model. The Production Readiness Review finds out which one it is, names what it takes to close, and prices it. Ship, fix and stop are all real verdicts.
- Do we need to be doing AI already?
- No. Most of what we build replaces work people currently do by hand, and plenty of our clients had no pilot and no shortlist when they called. That is what the AI Workflow Review is for: bring two or three workflows and we will tell you what each would cost to build, what it would save, and which one to do first.
- Do we have to be a research center or a government agency?
- No. We work with any organization trying to get AI into real use, and plenty of that work has nothing attached to it at all. Where a project does carry HIPAA or a state security review, that is the same build under harder conditions. You get the same standard either way.
- Can you work with our regulated data?
- We have designed and run HIPAA-compliant infrastructure holding live patient records for a state health department, on hardened AWS with unified security logging and single sign-on, and passed the state's security review to do it. We have also run FERPA-covered case management for a public school system. We build to that bar for every client, including the ones with no auditor to answer to, because it is the difference between a demo and a system.
- Are you SOC 2 certified?
- We hold a SOC 2 Type II report from Prescient Assurance dated 2024, and we are happy to send it to you. The practice behind it is current: we run HIPAA-compliant infrastructure holding live patient records today, hardened to CIS Level 1, and earlier this year we took a client through their own SOC 2 Type 2, running the penetration testing and answering the auditors directly on operational, configuration, and vendor-assessment controls. They passed. We renew our own attestation when an engagement calls for it rather than on a calendar, so tell us on the first call if your procurement needs a current one and we will tell you straight away what that takes.
- Can you be bought on a contract vehicle we already have?
- We hold Maryland CATS+ across all ten functional areas and we are registered in SAM.gov, both current. For a research center the work is usually funded straight from the grant, which avoids institutional procurement entirely. On SOC 2, see the answer above.
- How big is your team?
- Small, deliberately. Three senior people, a bench of fractional senior specialists we bring in per engagement, and the agent stack that runs our own operations. Nobody junior is looking for something to do on your budget. Every engagement is scoped against one workflow, priced as a fixed fee, and has a defined end.
- Do you write AI strategy documents?
- We build the systems a strategy document would describe. If what you need first is the list of which systems are worth building, in what order, that is the AI Workflow Review, and it comes with prices attached.
- What does it cost?
- Both reviews are $12,000, fixed, for two weeks. Neither is credited against later work. Builds are fixed-fee and scoped against one workflow, so you know the number before anyone starts, and we will give you a range on the first call rather than after three meetings.
Bring us one workflow that is costing you time.
Thirty minutes, no deck. You will leave the call knowing whether it is worth building, roughly what it would cost, and how long it would take.