.svg)
An AI-native platform purpose-built
for research team
Compeers is an AI-native, end-to-end insights platform that orchestrates multiple generative and deterministic models through agentic workflows to run custom research projects from design through reporting. Insights teams, marketing teams, and UX researchers use it to run their own studies. Teams that need capacity ask Compeers to run studies for them on the same platform.
The outcome you want, with the speed you need
Either way you get a complete study, a researcher's judgment at every step, and findings your stakeholders can act on, delivered in a fraction of the usual time and at lower cost, with no compromise on rigor or quality.
Compeers next to the status quo
Six to eight weeks for a typical custom study, whether run in-house across several tools or through an agency
Cut by 50 to 70 percent
Premium agency pricing with add-on fees for follow-up requests, or in-house time spent on manual work across disconnected tools
50 to 70 percent lower than an agency-run study when Compeers runs it, and far less researcher time per study when your team runs it, with no added charges for additional asks on a project
Varies by team and individual
Consistent across projects and across the people running them, with the same workflow each time
Each project starts mostly fresh
Past research and external context inform every study
Findings live in a static deck
Findings stay queryable through Savant after the readout
What you keep, what you get
What changes in your favor
Faster timelines, so stakeholders get answers when they need them.
Lower cost per study, so budget stretches to more research rather than less.
Consistent quality that does not depend on who is running the project or on churn in a vendor team.
Conclusions and recommendations grounded in your project data, prior research, and relevant external context.
A queryable record of the work that stays useful long after the reports are delivered.
What you do not give up
A researcher leading the project from kickoff through delivery, yours when your team runs it, ours when Compeers does.
Methodological rigor and the kind of finished deliverable a stakeholder can act on.
Custom work designed around your business question, not a templated workflow.
What you do not give up
A senior researcher leading the project from kickoff through delivery.
Methodological rigor and the kind of finished deliverable a stakeholder can act on.
Custom work designed around your business question, not a templated workflow.
Honest answers about the comparison
Compeers AI is AI-native rather than AI-retrofitted. AI is embedded into the research workflows from the ground up, rather than added on top of legacy processes.
For the user, that means less manual work, fewer disconnected steps, and faster progress from raw data to analysis and reporting. The AI assists throughout the process while preserving user control, so researchers spend more of their time on interpretation, stakeholder context, and strategic thinking rather than the mechanics of research.
No. Compeers AI uses real human respondents for primary research and does not use synthetic respondents as a substitute for real consumers. We use AI to make research faster and more efficient, including research design, data processing, analysis, coding, visualization, and reporting, but the underlying consumer input comes from real people. Our concern with synthetic respondents is fundamentally one of measurement.
Synthetic responses are model-generated approximations and can be affected by source data, prompting, model behavior, and other implementation choices. They can also compress real-world variation and produce responses that appear plausible without necessarily representing how actual consumers think or behave. While synthetic data may have value for exploration or narrowly defined applications, we do not believe it is currently a reliable general substitute for human respondents in primary market research.
For a deeper discussion of our position and the research behind it, see the articles on synthetic data and synthetic respondents in the Compeers AI blog, including Why Synthetic Respondents Fail the Test of Stable Measurement and How to Test Synthetic Respondents Without the Help of a Data Scientist.
Yes. The methodology, the analysis, and the final deliverable meet a rigorous professional standard, and a researcher reviews every stage before the project moves forward. When Compeers runs the study, that researcher is one of ours. When your team runs it, the platform enforces the same review points for your researcher.
The speed and cost savings come from using the right technology in the right places. The best way to evaluate Compeers AI is to use it with data from a project you have already completed and compare the reports it generates with your existing report.
Certain work, like data cleaning, crosstab analysis, and coding, is better handled by machines, since they are faster, more consistent, and less error-prone than manual processing. That frees the researcher to lead the study and focus on interpretation and strategy, which is where their judgment matters most.
Lower cost comes from removing the manual grind, not the expertise, and that holds whether the researcher is on your team or ours.
Yes. Once an MNDA is in place, share the data from a study you have already run. You will have a full report within the hour to judge against your original, before your first live project. Your team can run the comparison on the platform, or we can run it for you.
Test Compeers on a real study
A short conversation is enough to compare what Compeers and your current agency would each deliver on a question your team is already working through.
Enterprise-grade security
.svg)
Custom research, reimagined
.svg)
.svg)
.svg)
.svg)