Client case study
How SolutionStream made AI search visibility measurable.
New Reward measured how SolutionStream appeared across ChatGPT, Claude, Google AI, Grok, and Perplexity, then turned the result into a clear map of where the brand was recognized, cited, and still under-supported.
The business problem
Recognition was not the same thing as trust.
SolutionStream already had a strong public reputation for software delivery, staffing, and AI leadership. The open question was different: when a buyer asked an AI answer engine who to trust, could the engine find SolutionStream and support that answer with citations?
New Reward measured that question directly. The result showed a brand with strong AI recognition and a specific, measurable citation gap that could guide the next round of authority work.
Engine readout
The scan found the exact citation split.
Every engine did not behave the same way. That was the point. New Reward made the differences visible enough to act on.
ChatGPT
Recognized the brand, but rarely cited supporting sources.
Claude
Strong brand recognition and source trust.
Google AI
The strongest citation signal in the scan.
Grok
High visibility with a useful citation base.
Perplexity
The clearest citation repair opportunity.
What New Reward did
It became an operating map, not a vanity score.
The useful output was not one blended number. It was a precise view of where AI could mention SolutionStream, where it could cite the brand, and what needed to be strengthened next.
Measured the answer field
New Reward turned a fuzzy question into a repeatable read across five answer engines and buyer-style prompts.
Separated mentions from citations
The scan showed where AI knew SolutionStream and where it still lacked enough citation confidence to back the answer.
Packaged the next fixes
The operating layer produced packages, published data islands, and schema records that could support the next authority pass.
High-intent proof
The brand showed up beyond branded searches.
SolutionStream appeared on category and comparison prompts, including IT consulting, DevOps consulting, software engineering alternatives, and case-study research.
Operating sequence
A simple path from signal to next action.
Baseline the brand
Measure how often SolutionStream appeared when buyers asked AI engines about software development, IT consulting, and comparison searches.
Find the trust split
Compare mention coverage against citation coverage so the team could see which engines recognized the brand without supporting it.
Prioritize the repair
Use the engine-level gaps to shape the next content, source, entity, and technical-readiness work.
Generated assets
Measurement created a visible work queue.
The proof did not stop at a report. New Reward tracked the operating artifacts available for the next visibility and authority pass.
Packages created
Packages delivered
Packages downloaded
Published data islands
Schema records
Claim boundary
What this case study proves.
Supported claim
New Reward made SolutionStream visibility measurable across five answer engines, with quantified mention, citation, prompt, and engine-level proof.
Not claimed yet
This data does not claim traffic lift, search ranking lift, lead volume, pipeline, revenue, or deployed-schema impact. Those claims need implementation and attribution data.
New Reward for AI Search
See where AI mentions, cites, and trusts your brand.
Start with the visibility read. Leave with the first fix worth shipping.
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