AI Product Launch Support
The AI failure is not a crash. It is a wrong answer said confidently.
What is launch support?
Launch support means preparing an AI product for public release, covering both the technical behaviour under real load and whether the claims in your launch material match what the product genuinely does.
Ordinary software fails visibly. It errors, it times out, somebody sees a broken page. AI products fail differently, by answering confidently and incorrectly, which no load test detects and every user notices.
The second risk is the words. AI claims are unusually easy to overstate, and launch material is written weeks before anybody sees how the product behaves with real users. What is promised then becomes what customers hold you to.
There is a third that surprises people. A successful launch is also a bill, because AI running costs scale with use, and a product that goes further than expected can become a financial problem in its first week.
Why we raise unwelcome things before a launch
Duara supports AI product launches from Nairobi, covering the technical readiness and the accuracy of what is being claimed.
We will tell you a claim is not supportable, which is not always welcome close to a launch date. Marketing written before the product was finished usually promises something the product does not quite do, and customers find that faster than anybody expects.
Who this is for
- You are launching an AI product or feature
- Launch material was written before the build finished
- You expect a traffic spike you have not tested
- A previous launch produced problems you did not anticipate
Industries we serve
- Technology startups
- Financial services
- Telecommunications
- Retail and ecommerce
- Media
- Software companies
Problems this solves
These are the ways AI launches go wrong, and only one of them is technical in the ordinary sense.
- Wrong answers under real inputs. Load testing proves a system survives volume, not that it answers correctly, and real users produce inputs no test set contained.
- Claims the product cannot meet. Launch copy written before the build finished promises capability that does not quite exist, and customers hold you to the words.
- Cost scaling with success. AI running cost rises with use, so a launch that goes further than expected arrives as an invoice nobody modelled.
- No way to turn it off. When an AI feature misbehaves publicly, the choice is between leaving it running and taking down the whole product.
What we deliver
Behaviour tested on realistic inputs rather than volume alone, every launch claim checked against what the product does, running cost modelled at launch volume, and a way to disable the AI feature without downtime.
Behaviour tested on realistic and awkward inputs
Every launch claim checked against actual capability
Running cost modelled at expected launch volume
A way to disable the AI feature without downtime
Cover through the launch window
A written list of known weaknesses before you go live
Features
- Tested for wrong answers, not just crashes. The AI failure mode is confident and incorrect, which volume testing does not detect and users notice immediately.
- Claims checked line by line. Every sentence in the launch material is tested against what the product actually does, because customers hold you to the words.
- Cost modelled at launch volume. A launch that exceeds expectations becomes a bill, and knowing the figure beforehand turns a shock into a decision.
- A switch that turns it off. Being able to disable an AI feature without taking down the product is the difference between an incident and a crisis.
- Weaknesses written down first. A known list before launch lets you answer the first complaint properly rather than discovering the problem alongside your customers.
Benefits
- Fewer public failures. Testing awkward inputs finds the wrong answers before an audience does.
- Claims you can stand behind. Material that matches the product avoids the correction that costs more than a modest launch would have.
- No invoice shock. Modelled running cost means success arrives as a result rather than as a finance conversation.
- A calm launch week. Known weaknesses and a working off switch turn most launch problems into decisions somebody already considered.
What we check before launch
- Realistic input testing. Behaviour on messy, awkward and unexpected inputs rather than on the examples the product was built against.
- Load and failure behaviour. What happens under volume, and specifically what the product does when a dependency slows or stops.
- Claims review. Each statement in the launch material tested against demonstrated capability.
- Cost modelling. Running cost at expected launch volume, and at the volume you would consider a runaway success.
- Kill switch verification. Confirming the AI feature can actually be disabled without taking the product down with it.
The awkward inputs matter most. Real users type things no test set contains, and the first week of a launch produces more genuine edge cases than months of internal testing.
How the process works, step by step
Launch support usually starts two to four weeks before the date, with cover continuing through the launch window itself.
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Step 1
Free readiness conversation
We establish what is launching, when, and how much of the material is already committed.
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Step 2
Behaviour tested on hard inputs
Awkward and unexpected inputs rather than the examples the product was built to handle.
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Step 3
Claims checked against reality
Line by line, and we tell you which statements will not survive contact with customers.
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Step 4
Cost and shutdown verified
Running cost modelled at launch volume and the off switch proved to work.
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Step 5
Cover through the window
Support during the period when real users produce the problems testing did not.
Quality assurance and how we work
The commitments attached to standing next to somebody launch.
- We say when a claim is not supportable. It is rarely welcome close to a date, and a public correction costs considerably more than a modest launch would have.
- We do not call something ready when it is not. A date approaching does not change what the product does, and saying otherwise transfers the problem to your customers.
- We tell you what to cut when the date cannot move. Launching less that works beats launching everything and withdrawing part of it in week two.
- We give you the weakness list before you launch. You should know what can go wrong before your customers demonstrate it to you.
- We test for wrong answers rather than uptime alone. A system that stays up while answering incorrectly has failed in the way that matters here.
Frequently asked questions about launch support
Why is an AI launch different from a normal one?
The failure mode. Ordinary software errors visibly, while AI answers confidently and incorrectly, which no load test detects and every user notices.
Does load testing not cover this?
It proves the system survives volume. It says nothing about whether the answers are right, which is the part customers judge.
What is a claims review?
Each statement in your launch material checked against what the product demonstrably does, since customers hold you to the words.
What if we have already published the copy?
We still check it, and correcting a claim before launch is considerably cheaper than correcting it publicly afterwards.
Would you tell us to delay?
If the product is not ready, yes. A date approaching does not change what the product does.
What if the date genuinely cannot move?
Then we tell you what to cut. Launching less that works beats launching everything and withdrawing part of it in week two.
Why does cost come up at launch?
Because AI running cost rises with use, so a launch that exceeds expectations arrives as an invoice nobody modelled.
What volume do you model against?
Expected launch volume, and separately the volume you would consider a runaway success, since that is the case that hurts.
What is a kill switch for?
Disabling the AI feature without taking down the product, which is the difference between an incident and a crisis.
Do most products have one?
Fewer than you would expect, and it is usually straightforward to add before launch and awkward to add during one.
What inputs do you test with?
Messy, awkward and unexpected ones rather than the examples the product was built against, since users supply the former.
When should we bring you in?
Two to four weeks before the date. Earlier gives more room to act on what the review finds.
Do you cover the launch itself?
Yes, through the launch window, which is when real users produce the problems internal testing did not.
Will you find everything?
No. Real users generate more genuine edge cases in a week than months of internal testing, which is why the weakness list matters.
Can you help write honest launch copy?
We can tell you what is supportable. Writing it is usually better done by whoever knows the product voice.
Does this apply to an AI feature rather than a product?
Yes, and a feature inside an existing product carries more risk, since a failure affects something customers already rely on.
What about press and demonstrations?
A demonstration on chosen input is the easiest thing in the world to pass and tells you almost nothing about launch readiness.
Do you handle the marketing side?
We check accuracy rather than run campaigns. Whether a claim is true is a different question from whether it lands.
Who sees our unreleased product?
Only the people working on the review, under whatever confidentiality terms you set before we start.
What does launch support cost?
Scope and how long the cover runs determine it, quoted after the readiness conversation.
Glossary of terms
Launch terms in plain language.
- Confidently wrong
- An AI answer that is incorrect but presented with no sign of uncertainty, which is the characteristic failure.
- Kill switch
- A way to disable one feature without taking down the product around it.
- Launch window
- The first days of public availability, when real users produce the inputs testing did not.
- Claims review
- Checking each statement in launch material against what the product demonstrably does.
- Runaway success cost
- What the product costs to run if it goes considerably further than expected.
- Edge case
- An unusual input that behaves differently, of which real users produce far more than any test set.
Related services in AI Events
Talk to us about launch support
Take your launch page and mark every sentence the product cannot yet do. That list is the launch risk.
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