#599 Palantir in Ottawa?

Could Palantir-style technology help run Ottawa?

The city is a mess, and a new way of managing it is worth discussing. The idea behind the software matters more than the brand name on the contract.

Palantir’s CEO, Alex Karp, has been in the news again. On the company’s third-quarter earnings call on November 2, he argued that governments buying their own AI infrastructure is the company’s defining opportunity. He called it “Sovereign AI.” Reports on the call also said U.S. commercial revenue of $984 million outgrew the government book for the first time.

Karp is not an easy speaker to follow, so here is the plain version. Palantir sells software that pulls an organization’s scattered data into one place, builds a model of how that organization works, and lets people, and increasingly AI, make decisions on top of it. For a city that struggles to see how its own departments connect, that is worth thinking about.

What Palantir actually sells

Gotham

The original product, built for intelligence, military and law enforcement users. It connects data from many sources so analysts can see relationships and plan operations.

Foundry

The civilian and commercial version. It merges data from different systems, such as inventory, finance, patient records and supply chains, and builds workflows on top.

Ontology

A digital map of the organization: the real-world things it cares about (shipments, hospital beds, buses) and how they relate. It is the layer that lets software and AI “understand” the business.

AIP

Connects large language models to that map, so an AI can answer questions or take actions using the organization’s own data, within permissions and controls.

Apollo

The deployment layer that keeps the software running across cloud, on-premises and secure environments.

The idea: run the city as one connected system

Most city departments run their own systems, budgets and metrics. Nobody sees how a decision in one place affects another. A connected model would work differently:

• One shared data model of the city, where every asset, service request, project and budget line is a connected record.
• Decisions tied to live data instead of annual reports.
• Departments measured on outcomes, such as response times, backlogs and cost per result, and benchmarked against comparable cities.
• Public accountability built in, so residents can see the same core numbers council sees.

Where it could apply: transit, housing and policing

Transit

This is the best fit, because the data is mostly operational and not about individuals. Linking vehicle location, ridership, maintenance records, LRT fault logs, schedules and road works could predict breakdowns, show where buses lose time, and support a public reliability scorecard. The main risks are vendor lock-in and metrics being gamed, not privacy.

Housing

The data exists, but it is spread across many bodies. Connecting the housing registry waitlist, shelter occupancy, social housing repairs and vacancies, building permits and approvals would show where the pipeline actually jams: approvals, financing, repairs or intake. The risk is personal data. Records about shelter use and benefits are sensitive, so access limits and aggregation by default are essential.

Policing

This is where the same technology is most controversial. The strongest low-risk uses are workload and response-time analysis, overtime and budget tracking, and linking police, paramedic, mental health and housing data to find calls that would be better handled by someone else. The high-risk uses are predictive policing and individual risk-scoring. Critics argue these tend to reproduce where police have historically looked, not where crime actually is. If any police use goes ahead, it needs public rules on what data can be linked, independent audit, civilian oversight and no secret contracts.

The payoff across all three is that one person can appear in the shelter, emergency-call and hospital systems at once, and today nobody sees the total cost or the pattern. A connected model makes that visible, which is what lets a city shift money toward prevention. It is also the part that needs the strictest privacy rules.

Why it is a hard sell

• Cost and fit. Palantir is built for very large clients such as militaries, national health systems and big corporations. A municipality may get most of the benefit from cheaper, simpler tools or from fixing its own data problems first.
• Lock-in. Once a city’s data is modelled in a vendor’s proprietary layer, switching away is hard and expensive.
• Data sovereignty. Experts have raised the concern that a 2018 U.S. law could compel American companies to hand data to the U.S. government, wherever it is stored. Municipal data includes sensitive information about residents, and the federal government has promised its own data sovereignty strategy.
• Transparency. Federal dealings with Palantir have drawn criticism for how quietly they were done. Reporting found that National Defence quietly extended a Gotham deal a dozen times between 2020 and 2025, with its estimated value rising from $14.4 million to $44.4 million, and that a separate $3.7 million contract surfaced only after an MP asked about federal AI contracts.
• The other view. The Defence Minister has defended the newer contract as a legitimate procurement with Palantir’s Canadian branch. Supporters of the technology point to its record on large, complicated data problems.

The software is the easy 20 percent. Most government digital transformations fail because departments won’t share data, metrics get gamed, procurement locks the city into one vendor, or a platform gets bought without anyone changing how decisions are made.

A 90-day pilot

If Ottawa wanted to test this, the aim should be real results and clear rules before anything large is bought.

Days 1 to 30: foundations and rules

• Name one accountable executive, a small cross-department team, and an independent privacy and legal adviser.
• Publish the principles first: Canadian data residency, no secret contracts, privacy impact assessments, aggregated data by default, a public register of what data is linked and why, and an exit plan for any vendor.
• Inventory the data in transit, housing and policing: who owns it, what it holds, how clean it is, and what legal limits apply. This step needs no software and is usually the most revealing.
• Choose two or three specific questions and set baseline metrics, such as why a development permit takes as long as it does at each step, or where transit loses the most time.

Days 31 to 60: build a small, real version

• Start with transit as the quick win: link vehicle, schedule and maintenance data and publish one reliability scorecard.
• Build the housing pipeline view using aggregate data only.
• For policing, do governance and analysis only: workload, response times and call types. No predictive or individual-level tools.
• Use cheap, replaceable tools: open data standards, a city-controlled data layer, hosted in Canada. Any vendor demo, Palantir’s included, should be a bounded trial with no long-term commitment.

Days 61 to 90: test, publish, decide

• Use the integrated view on two or three real operating or budget decisions and see whether it changed them.
• Publish a results report covering what worked, the data-quality problems and the cost.
• Get an independent review and open it to council and public questions.
• Make a go or no-go call on scaling, with a procurement process that compares options instead of defaulting to one vendor.

Success at day 90 would be a public dashboard residents can use, a documented data inventory the city didn’t have before, one or two visibly better-informed decisions, a governance framework that survives scrutiny, and an evidence-based answer to whether a big platform is needed or lighter tools do the job.

The bottom line

Ottawa needs a better way to see and manage itself, and a connected, outcome-based model is a reasonable direction. But the paradigm is the valuable part, not any one product. A city can adopt the approach with a city-owned data layer, open standards and Canadian hosting, and keep control of its own data and its own decisions. Whether Palantir has a role should be decided by an open comparison against those alternatives, in public, and not by a quiet contract.

Sources

• 24/7 Wall St.: Karp bets on Sovereign AI as Palantir’s next growth engine (November 2, 2026)
• 24/7 Wall St.: Palantir Q3 2026, commercial revenue tops government for the first time
• The Peak: Why are security experts worried about Canada’s secret Palantir contracts? (June 6, 2026)
• Investigative Journalism Foundation: NDP’s Lewis slams secret federal contract with Palantir (June 5, 2026)
• Toronto Star reporting on the Defence Department’s $3.7 million Palantir contract and the Defence Minister’s response (2026)

Based on the above and Dr. Karp's sales pitch, why should Ottawa choose Palantir blog and Karp’s recent pitch is that Ottawa should not default to “choose Palantir.” It should test whether a Palantir-style connected data model delivers measurable operational gains under public rules, city control, and open comparison—then decide. The valuable part is running the city as one shared data model (an “Ontology” of objects, links, and actions) with live data, outcome metrics, and public accountability, instead of siloed departmental systems.
Transit: Link operational data for predictions and public scorecards (lower privacy risk).

Housing: Connect waitlists, permits, and outcomes to surface bottlenecks (use aggregates where possible).

Policing: Low-risk uses like workload and response analysis; high-risk predictive tools would need strict public rules, independent audits, and civilian oversight.

The payoff described is visibility into patterns that no single department currently sees (e.g., the same person appearing across shelter, emergency, and hospital systems, and the total cost or trajectory). 

Note that many government digital projects fail because of data-sharing problems, gamed metrics, or poor procurement, not lack of software.⁠Peterkarwacki.blogspot

The counter-arguments: high cost and questionable municipal fit, vendor lock-in, data-sovereignty exposure under U.S. law, transparency problems (quiet federal extensions of Gotham deals, late revelations of contract values), and bias risks in any predictive policing use. 

The recommended path is a 90-day pilot (data inventory and rules → small working versions → published results and open comparison) with Canadian residency principles, city-owned layers where feasible, and no secret contracts.⁠Peterkarwacki.blogspot

Bottom line in the post: “The paradigm is the valuable part, not any one product… 

Whether Palantir has a role should be decided by an open comparison against those alternatives, in public, and not by a quiet contract.”

What Karp’s recent sales pitch adds

On the Q3 2026 earnings call (the one the post references), Karp framed “Sovereign AI” as a defining opportunity and noted that U.S. commercial revenue ($984 million) had overtaken government revenue for the first time. The pitch emphasizes rapid value through intensive bootcamps rather than long traditional pilots, an Ontology that lets organizations (or partners) build operational AI on their own data, and the ability to turn pilots into production contracts quickly. 

He has also criticized slow AI adoption outside the U.S. and China (including in Canada), arguing that hesitancy creates political and economic pressure.⁠Peterkarwacki.blogspot

In other words, the commercial pitch is: the platform already works at scale for complex operational problems, customers can get results fast, and “sovereign” deployment options exist.

Combined case for why Ottawa might choose it (under these conditions)

1. It matches the problem diagnosed — Ottawa’s data is fragmented across transit, housing, social services, and policing. A working Ontology + decision layer can surface total costs and patterns that siloed systems hide, supporting the shift toward prevention and outcome measurement you describe.
2. Proven on large, messy data problems — Federal defence use (and the Defence Minister’s defense of it as legitimate) is cited as evidence that the tools handle serious data environments. Commercial traction supports the claim that it is not only a government specialty product.
3. Speed of value — Karp’s bootcamp/model is designed to produce usable results quickly rather than multi-year IT projects that often fail. Your 90-day pilot structure is compatible with that approach.
4. Accountability potential — Public dashboards, published inventories, and outcome scorecards (transit, housing bottlenecks) can be built on top of the model if the city insists on them from day one.

The constraints the blog itself imposes

Even the positive case is conditional. Choosing Palantir only makes sense if the city keeps control (data residency, open standards or export paths to limit lock-in), runs a transparent pilot with published results and competing options, restricts high-risk uses (especially predictive policing), and treats any contract as a public decision rather than a quiet extension. The federal record of under-disclosed or quietly expanded deals is exactly the pattern your post flags as a problem.

Net: based on the blog + Karp’s pitch, Ottawa should choose the connected, outcome-oriented operating model. It should choose Palantir only if a short, public, controlled pilot shows it is the best practical way to get that model, with the city’s data and decision rights protected. The brand is secondary to the paradigm and the process.

i 

 In 2026, Palantir Technologies CEO Dr. Alex Karp public messaging has centered around geopolitical techno-nationalism, the "Sovereign AI" movement, a massive cultural manifesto.

The core themes

1. The "Sovereign AI" Manifesto (The Technological Republic)
A 22-point manifesto on X summarizing Karp’s core philosophical work,
The Technological Republic.  Karp's stance on tech and governance: [1, 2, 3]
The "Moral Debt" of Tech: Karp claimed that Silicon Valley engineering elites owe a moral debt to the United States and have an absolute obligation to build software for national defense rather than just creating consumer applications and "the tyranny of apps". [1, 2, 3]
Hard Power and Warfare: He asserted that the survival of democratic societies requires hard power built on software, stating that AI weapons will be built and western nations cannot pause for "theatrical debates" while adversaries move ahead. [1, 2, 3]
Universal National Service: Karp advocated for moving away from an all-volunteer military, suggesting society seriously consider reinstating a universal national draft so all citizens share the risk of future conflicts. [1, 2, 3]

Cultural Superiority: He stirred controversy by criticizing post-WWII pacifism/disarmament in Germany and Japan, arguing that some cultures are "harmful" or "middling" and that hollow pluralism must be rejected in favor of Western strength. [1, 2, 3]
2. Geopolitics & AI Dynamics ("Us vs. Them")
Karp has consistently framed the ongoing AI race as a binary, high-stakes battle for global dominance: [1, 2]

The China Threat: In several forums, Karp warned that China is "doing exceedingly well at AI," calling it a "super high IQ scaled culture". He bluntly summarized the geopolitical reality as an "us or them" scenario where American technological supremacy is the only thing capable of preventing global wars. [1]

Support for Allies: Karp reiterated his fierce public alignment with Israel and Western defense forces, asserting that Palantir is proud to serve the "warfighter" directly on the front lines in modern conflicts (such as Ukraine). [1, 2, 3]
3. Corporate AI Reality vs. "Selling Crap"
Karp has sharply criticized how the broader tech industry approaches enterprise AI, distinguishing Palantir's Artificial Intelligence Platform (AIP) from its competitors: [1, 2]

Condemning Frontier Labs: Karp ripped standard frontier AI labs for trying to "colonize your enterprise" by convincing companies to pay for expensive tokens that effectively transfer corporate intellectual property and alpha to the tech giants. [1, 2]

Fixing How AI is Sold: During a CNBC interview, he stated that "something has gone completely wrong" with the way AI is currently being marketed and sold, arguing that most products fail to translate into tangible, real-world utility. [1]
4. Financial "Vindication" and Taunting Wall Street
Following Palantir's extraordinary Q3 2026 earnings report—where revenue grew 96% year-over-year and commercial sales surpassed government sales for the first time—Karp took a victory lap: [1, 2]

The Binary Future: In his Q3 Letter to Shareholders, Karp noted that the AI revolution is creating a stark divide between the "haves and have-nots," writing that legacy companies who fail to adapt face a "lonely middle" that is "little more than a barren wasteland".

Insatiable Demand: He noted on earnings calls that demand for Palantir’s products is entirely "insatiable" and far larger than the company has the capacity to service.

A Message to Short-Sellers: At the close of the November 2026 earnings call, Karp bypassed traditional Wall Street analysts to speak directly to retail investors. He thanked early backers for defending the company against "ridiculously stupid and malicious" attacks, adding: "Part of what motivates me is helping to make sure we are fighting for you and, quite frankly, making sure that the people that made fun of you and made fun of us are suffering." [1, 2, 3, 4, 5]

5. Career & Job Advice in the AI Era
Karp has also offered blunt assessments regarding how AI will reshape human labor, challenging conventional Western assumptions: [1, 2]
The Death of Elite Humanities: Speaking on the impact of AI on white-collar jobs, Karp noted that AI will heavily disrupt roles relying solely on theoretical knowledge. He used himself as an example, stating: "You went to an elite school, and you studied philosophy... Hopefully, you have some other skill. That one is going to be hard to market." [1, 2]
The Rise of Vocational and Neurodivergent Workers: Conversely, Karp argued that the individuals who will thrive most in the AI era are those with technical vocational training (who can be rapidly upskilled by AI) and neurodivergent individuals with unique, outlier cognitive aptitudes. [1, 2]

 Palantir's 22-point summary of Karp's book:

1. Silicon Valley owes a moral debt to the country that made its rise possible. The engineering elite of Silicon Valley has an affirmative obligation to participate in the defense of the nation.

2. We must rebel against the tyranny of the apps. Is the iPhone our greatest creative if not crowning achievement as a civilization? The object has changed our lives, but it may also now be limiting and constraining our sense of the possible.

3. Free email is not enough. The decadence of a culture or civilization, and indeed its ruling class, will be forgiven only if that culture is capable of delivering economic growth and security for the public.

4. The limits of soft power, of soaring rhetoric alone, have been exposed. The ability of free and democratic societies to prevail requires something more than moral appeal. It requires hard power, and hard power in this century will be built on software.

5. The question is not whether A.I. weapons will be built; it is who will build them and for what purpose. Our adversaries will not pause to indulge in theatrical debates about the merits of developing technologies with critical military and national security applications. They will proceed.

6. National service should be a universal duty. We should, as a society, seriously consider moving away from an all-volunteer force and only fight the next war if everyone shares in the risk and the cost.

7. If a U.S. Marine asks for a better rifle, we should build it; and the same goes for software. We should as a country be capable of continuing a debate about the appropriateness of military action abroad while remaining unflinching in our commitment to those we have asked to step into harm's way.

8. Public servants need not be our priests. Any business that compensated its employees in the way that the federal government compensates public servants would struggle to survive.

9. We should show far more grace towards those who have subjected themselves to public life. The eradication of any space for forgiveness—a jettisoning of any tolerance for the complexities and contradictions of the human psyche—may leave us with a cast of characters at the helm we will grow to regret.

10. The psychologization of modern politics is leading us astray. Those who look to the political arena to nourish their soul and sense of self, who rely too heavily on their internal life finding expression in people they may never meet, will be left disappointed.

11. Our society has grown too eager to hasten, and is often gleeful at, the demise of its enemies. The vanquishing of an opponent is a moment to pause, not rejoice.

12. The atomic age is ending. One age of deterrence, the atomic age, is ending, and a new era of deterrence built on A.I. is set to begin.

13. No other country in the history of the world has advanced progressive values more than this one. The United States is far from perfect. But it is easy to forget how much more opportunity exists in this country for those who are not hereditary elites than in any other nation on the planet.

14. American power has made possible an extraordinarily long peace. Too many have forgotten or perhaps take for granted that nearly a century of some version of peace has prevailed in the world without a great power military conflict. At least three generations — billions of people and their children and now grandchildren — have never known a world war.

15. The postwar neutering of Germany and Japan must be undone. The defanging of Germany was an overcorrection for which Europe is now paying a heavy price. A similar and highly theatrical commitment to Japanese pacifism will, if maintained, also threaten to shift the balance of power in Asia.

16. We should applaud those who attempt to build where the market has failed to act. The culture almost snickers at Musk's interest in grand narrative, as if billionaires ought to simply stay in their lane of enriching themselves . . . . Any curiosity or genuine interest in the value of what he has created is essentially dismissed, or perhaps lurks from beneath a thinly veiled scorn.

17. Silicon Valley must play a role in addressing violent crime. Many politicians across the United States have essentially shrugged when it comes to violent crime, abandoning any serious efforts to address the problem or take on any risk with their constituencies or donors in coming up with solutions and experiments in what should be a desperate bid to save lives.

18. The ruthless exposure of the private lives of public figures drives far too much talent away from government service. The public arena—and the shallow and petty assaults against those who dare to do something other than enrich themselves—has become so unforgiving that the republic is left with a significant roster of ineffectual, empty vessels whose ambition one would forgive if there were any genuine belief structure lurking within.

19. The caution in public life that we unwittingly encourage is corrosive. Those who say nothing wrong often say nothing much at all.

20. The pervasive intolerance of religious belief in certain circles must be resisted. The elite's intolerance of religious belief is perhaps one of the most telling signs that its political project constitutes a less open intellectual movement than many within it would claim.

21. Some cultures have produced vital advances; others remain dysfunctional and regressive. All cultures are now equal. Criticism and value judgments are forbidden. Yet this new dogma glosses over the fact that certain cultures and indeed subcultures . . . have produced wonders. Others have proven middling, and worse, regressive and harmful.

22. We must resist the shallow temptation of a vacant and hollow pluralism. We, in America and more broadly the West, have for the past half century resisted defining national cultures in the name of inclusivity. But inclusion into what?
1, 2, 3, 4, 5]





5. Career & Job Advice in the AI Era
Karp has also offered blunt assessments regarding how AI will reshape human labor, challenging conventional Western assumptions: [1, 2]
The Death of Elite Humanities: Speaking on the impact of AI on white-collar jobs, Karp noted that AI will heavily disrupt roles relying solely on theoretical knowledge. He used himself as an example, stating: "You went to an elite school, and you studied philosophy... Hopefully, you have some other skill. That one is going to be hard to market." [1, 2]
The Rise of Vocational and Neurodivergent Workers: Conversely, Karp argued that the individuals who will thrive most in the AI era are those with technical vocational training (who can be rapidly upskilled by AI) and neurodivergent individuals with unique, outlier cognitive aptitudes. [1, 2]