Buyer's guide
The best decision intelligence platforms in 2026
Decision intelligence is a crowded label, and most products wearing it are reporting tools with an assistant attached. The test that separates them is simple: does it compute why a number moved, and can it be held to that figure?
Last reviewed 3 August 2026
The short answer
Palantir is the only option here that will build you a bespoke operational system, and it is priced accordingly. Tellius is the closest genuine neighbor on automated root cause. Dataiku and Databricks are platforms for people who build models rather than people who act on them. Most of the rest are business intelligence tools with an assistant added. SQOR.ai is built for the case where you want causation, prediction and a scored action on every metric, with no semantic model built by hand and every figure reconciled to the ledger.
| Platform | What it computes | Who models the data | Recommends actions | Fully-loaded cost, 25 users | Time to value |
|---|---|---|---|---|---|
| SQOR.ai | Metric, drivers, forecast, scored action | Nobody. The platform generates it | Yes, scored with a confidence and a value | $48,960 all-in, 25 users | Two weeks |
| Palantir Foundry | Bespoke operational models | Their embedded engineers | Yes, within the system they build | $1,225,000 fully loaded | Quarters |
| Tellius | Automated root cause on modelled views | Your team, as Business Views | Insights and drivers, not scored actions | $277,560 fully loaded | Months |
| ThoughtSpot | Search answers and change analysis | Your team | Change analysis, not scored actions | $368,750 fully loaded | Months |
| Domo | Dashboards, alerts, apps | Your team | Alerts, not scored actions | $285,500 fully loaded | Months |
| Dataiku | Models your data scientists build | Your data science team | Whatever your team builds | $384,648 fully loaded | Quarters |
| Databricks | Whatever you engineer on it | Your platform team | Whatever your team builds | $281,750 fully loaded | Quarters |
| Pyramid Analytics | Dashboards and analytics | Your team | No | $225,000 fully loaded | Months |
| Sisense | Embedded dashboards | Your team | No | Not published | Months |
| Alteryx | Prepared datasets and workflows | Your analysts | No | $274,353 fully loaded | Months |
Fully-loaded cost is the license or platform fee plus the compute underneath plus a data engineer and analyst at $225,000 a year, applied identically to every row. Payback. The subscription is $48,960 a year for 25 users all-in, and set-up is a nominal fee that covers the proof of concept. Against the cheapest fully-loaded stack on this page the annual difference is more than $175,000 a year, which is over three times the whole SQOR.ai subscription. That is arithmetic on the figures in the table above, not a projection.
Every option
Ten platforms, and what each one really does.
Read the middle column of the table before the price column. Whether a platform computes causation or merely displays correlation is the difference between decision intelligence and a dashboard with a chat box.
1. SQOR.ai
Our pickOn the decision-intelligence test it is the only option here that computes causation, forecast and a scored action on every metric without a model somebody built first.
Best at
Generating the whole measurement layer itself and answering in plain language, with every figure computed by machine learning and reconciled to your ledger. It is the only option here that requires no semantic model built by a person first.
What it costs
$48,960 a year all-in for 25 users, priced on query volume rather than seats, with the data warehouse included and seats unlimited. Onboarding is a nominal set-up fee that covers the proof of concept. Fully loaded that lands at roughly a fifth to a twentieth of the stacks below, because there is no separate warehouse bill and no data team to staff.
Where it fits
Any company on the cloud that wants the answer rather than another tool to run. It is strongest where the business is complex, the systems are many, and nobody wants to fund a data team just to see what is happening: mid-market through enterprise, multi-site and multi-entity operators, and whole portfolios for private-equity and venture investors. It sits beside your audited books and reads read-only, so it goes in without a replatforming project and without touching your source of truth.
2. Palantir Foundry
It passes the decision-intelligence test comprehensively and prices like a bespoke program, because that is what it is.
Best at
Bespoke operational systems at national scale. When the problem is unique and the budget is unlimited, nobody else does what they do.
What it costs
Charged at the very bottom of Palantir's own smallest deal band, $1,000,000 (REPORTED), plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE). Fully loaded, $1,225,000.
Do not buy it if
you do not want engineers embedded in your business for months. The forward-deployed model is the delivery mechanism, not an add-on.
3. Tellius
The closest genuine competitor on this page. It computes root cause, and it computes it on a model your team maintains.
Best at
Automated root-cause analysis. Of everything on this list it is the closest neighbor to what SQOR does, and its automated insights are good.
What it costs
Tellius' own AWS starting rate of $6 an hour, running always-on, is $52,560 a year (DERIVED), plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE). Fully loaded, $277,560.
Do not buy it if
you have no data team. Tellius answers against Business Views that somebody models first, which is exactly the work SQOR removes.
4. ThoughtSpot
It answers questions well and stops short of scoring an action, which is the line between search and decision intelligence.
Best at
Search-driven analytics. They pioneered typing a question instead of building a chart, and the search experience is mature.
What it costs
Vendr reports an average Enterprise contract of $137,000 (REPORTED), plus the warehouse at about $6,750 for this usage (DERIVED), plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE). Fully loaded, $368,750. Note the Pro tier's Spotter allowance is 25 questions a month.
Do not buy it if
you have no semantic model. ThoughtSpot answers against a model your team builds and maintains first, so the setup work does not disappear.
5. Domo
Alerting is not recommendation. Domo tells you a threshold was crossed and leaves the reasoning with you.
Best at
Breadth. Connectors, ETL, dashboards and an app layer in one place, which suits an organization that wants a single vendor for the whole chain.
What it costs
Vendr reports a median of $60,500 (REPORTED), plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE). Fully loaded, $285,500. Users report the credit model is hard to predict, with renewal increases reported from 150 percent up to 1,120 percent.
Do not buy it if
you need budget certainty. The credit consumption model is the most common complaint in public reviews.
6. Dataiku
It will do all of this if your data scientists build it, which makes the platform the toolkit rather than the answer.
Best at
Data science teamwork. For a real data-science function it is an excellent shared workbench and the collaboration model is well designed.
What it costs
Vendr reports a median of $159,648 (REPORTED) with no published price, plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE). Fully loaded, $384,648.
Do not buy it if
your users are business leaders. This is a specialists' platform, shaped for the people who build models rather than the people who act on them.
7. Databricks
Same judgement as Dataiku with a stronger engineering floor: capability without an opinion.
Best at
Engineering data at scale, and machine learning on it. If you have petabytes and a platform team, this is a serious platform and the lakehouse argument is real.
What it costs
A mid-market DBU and compute figure of $50,000 (ESTIMATE), plus the Genie question meter at about $6,750 for this usage per Databricks' own documentation (DERIVED), plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE). Fully loaded, $281,750.
Do not buy it if
your problem is business questions rather than data engineering. This is a platform for people who build platforms.
8. Pyramid Analytics
It sits in this comparison on breadth rather than on causation, and the roadmap question now belongs to ServiceNow.
Best at
Value for money before the acquisition, and users genuinely liked the price. A capable, well-regarded platform.
What it costs
Charged at zero for the platform, plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE). Fully loaded, $225,000, which is less than the payroll alone.
Do not buy it if
you need roadmap certainty. Following the ServiceNow acquisition, direction is set by ServiceNow's stated plans rather than by Pyramid.
9. Sisense
In this category it is really an embedding specialist, so judge it on what your customers see rather than on what your operators decide.
Best at
Embedded analytics. If you are putting dashboards inside your own product for your customers, this is a specialist at it.
What it costs
Sisense does not publish pricing and we have no sourced third-party figure, so no number is shown here. Expect a platform fee plus the infrastructure beneath it, plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE).
Do not buy it if
your use case is internal decision-making. The embedding strength is aimed at your product, not your operators.
10. Alteryx
It prepares the data that a decision platform would reason over, which makes it upstream of this comparison rather than in it.
Best at
Analyst workflow craft. For the person who builds the data preparation, it is a strong tool with a loyal following.
What it costs
Vendr reports a live median contract of $49,353 (REPORTED), plus the roughly $80,000 server users report, plus the data engineer and analyst it takes to turn it into answers, modelled at $225,000 a year (ESTIMATE). Fully loaded, $274,353.
Do not buy it if
you want answers rather than workflows. Alteryx licenses the analysts who build each workflow, so headcount is effectively the meter.
How to choose
Four questions that separate decision intelligence from reporting.
One, does it compute the drivers behind a number, or show you correlated charts and leave the reasoning to you? Two, does it produce a recommended action with a confidence and a value attached, or an observation? Three, who builds the model, and is that a role you are willing to fund permanently?
Four, and this is the one that catches people: what happens when it cannot reconcile a figure? A platform that guesses to fill the gap is worse than one that says nothing, because you cannot tell the difference from the outside. Insist on a demonstration of the failure case, not the happy path.
Questions
Decision intelligence, asked plainly.
What is a decision intelligence platform?
A decision intelligence platform does three things a reporting tool does not: it computes why a number moved rather than only showing that it moved, it forecasts where the number is heading, and it recommends an action with a confidence and an expected value attached. If a product only visualizes history and adds a chat interface, it is business intelligence with an assistant, whatever the label says.
How is decision intelligence different from business intelligence?
Business intelligence answers what happened. Decision intelligence answers why it happened, what happens next, and what to do about it, and it attaches a confidence to each. The practical test is whether the causation is computed or narrated: a language model can write a plausible explanation of any chart, which is not the same as measuring which drivers moved the number.
Which decision intelligence platform needs no data team?
Almost all of them need one, which is the part the category tends not to advertise. Tellius answers against Business Views somebody models, Dataiku and Databricks are built for specialists, and Palantir supplies the specialists themselves as embedded engineers. SQOR.ai generates the measurement layer from your own data, which is why it requires no data specialist on your side.
Can a decision intelligence platform be trusted with financial numbers?
Only if the number is not generated by a language model. In SQOR.ai machine learning computes each figure and reconciles it to your general ledger, the language model explains it and never holds it, and when a figure cannot be reconciled the platform withholds it and says so. It also sits beside your audited books and never writes to them, which is the boundary any finance function will ask about first.
What does a decision intelligence platform cost?
The range on this page runs from $225,000 to $1,225,000 a year fully loaded, and the spread is mostly labor rather than license. Palantir sits at the top because embedded engineers are the delivery model. SQOR.ai is $48,960 a year for 25 users all-in with the warehouse included, which is the outlier precisely because there is no data team line to add.
Is Gartner's view of this category published?
Gartner covers adjacent categories in its 2026 Hype Cycles for Analytics and Business Intelligence and for Data Science and Machine Learning. SQOR.ai is named in both, and is named as a Sample Vendor in the Vibe Analytics profile, a category Gartner rates Transformational, which is its highest benefit rating. Gartner does not endorse any vendor.
Test the failure case, not the demo.
Ask us a question we cannot reconcile and watch what happens. That is the only part of an evaluation that tells you anything.