Comparison
Unloq and IBM Decision Intelligence compared
IBM Decision Intelligence turns written policies into automated decision services, like a discount calculator or car loan approval. Unloq is a decision intelligence platform that shows a leadership team why a number moved, ranks the options and measures what each decision was worth. Use IBM to run a policy at scale and Unloq to work out what it should say.
Which decisions suit IBM Decision Intelligence, and which suit Unloq?
Decisions that repeat under a rule you have already written suit IBM. Unloq is built for the judgement calls leaders have to make and then defend.
The decision | Better fit | Why, from each company’s own pages |
|---|---|---|
Routine approvals or prices under a written policy, such as a loan or a discount | IBM Decision Intelligence | IBM turns “policies written in natural language” into “governed, auditable decision flows” that applications call as web services |
Checking a request or a supplier against fixed rules | IBM Decision Intelligence | IBM’s samples include supplier compliance validation, and one flow can combine rules, machine learning models and generative AI |
A decision an AI agent calls as a governed step | IBM Decision Intelligence | IBM provides MCP servers for its decision services |
Why a business number moved | Unloq | Unloq ranks the drivers by their share of the change, calculated in SQL, and sets your figures beside the market |
Which option to back on a leadership call | Unloq | Options come ranked best first, with odds checked against your own history and tested against your budgets and limits |
Whether a leadership call paid off | Unloq | Unloq keeps the outcome expected at approval and measures what the decision added against a baseline agreed before acting |
Setting a new policy, then running it | Both, in that order | Unloq weighs the options and records the approval; IBM’s engine then runs the policy |
When does IBM Decision Intelligence fit better?
IBM fits better when a decision repeats under a policy you already know and every outcome has to be traceable. IBM’s own samples run from a car loan approval to an MRI request.
The logic has to be audited. IBM describes “full lifecycle traceability”, from policy creation to business outcome, with role-based access control and testing before deployment.
You already run IBM decision software. The client-managed edition is “formerly known as IBM Automation Decision Services” and runs on Kubernetes, serverless or Cloud Pak for Business Automation on Red Hat OpenShift, and IBM’s solutions page groups it with Operational Decision Manager.
You want to measure each automated decision. IBM’s product page lists Decision Insights, to “Monitor your decision performance to measure the impact”.
You want your own models in the flow. IBM lets you bring your own machine learning models into a decision service.
You want to start without a sales call. IBM publishes a price and a 30-day full-feature trial for its software-as-a-service edition (pricing).
When does Unloq fit better?
Unloq’s job starts where no rule covers the decision yet and the people making it will have to defend it afterwards. Most businesses we work with already hold years of sales figures and reports, and the email to go with them. Unloq starts from those records, connecting read-only to the systems you approve. Ask why margin fell and Unloq ranks the drivers by their share of the fall; ask what to do and the options come ranked best first, each with its evidence. Where there is not enough history, Unloq says so and gives no number. A person signs off every decision, and Unloq records what that person expected and later measures what the decision added.
Can you use IBM Decision Intelligence and Unloq together?
Yes, in sequence: Unloq helps a leadership team work out what a policy should say, and IBM’s engine runs the policy from then on. IBM’s product page says you can “Turn business policies into AI-authored decisions in hours.” The hours start once someone has agreed what the policy says, and reaching that agreement is the part Unloq works on.
Take a discount policy. An exception to it can be a judgement call the first time and a rule by the tenth, and we cannot tell you in advance which one you are facing. Margin has slipped, and Unloq ranks the drivers by their share of the fall. If discounting is one of them, Unloq puts options to the leadership team, such as a lower ceiling or a threshold set by customer type, each with the evidence behind it and its odds. Someone approves one, and Unloq records what it is expected to do to margin. Your team then writes the approved rule into IBM as a policy, IBM’s Decision Assistant turns the policy text into decision logic, and a decision service applies it to every quote. A quarter later, Unloq measures what the change added against the baseline agreed before acting.
Questions we get asked
Bring us a decision that has no rule yet
If you are weighing up a call that no policy covers, bring it to us and we will show you what Unloq does with it.
Compared on 30 October 2026 from each company’s public pages; corrections are welcome at hello@unloq.co. IBM and IBM Decision Intelligence are trademarks of their owner, and Unloq is not affiliated with IBM.