Cassi.ai blog
The Cassi.ai blog publishes practical material about AI engineering for market research, consumer insights, synthetic data, research automation, and responsible deployment. Articles provide context for teams evaluating an AI research workflow or looking for ways to connect research practice with data and model operations.
For a project-specific discussion, use the contact route instead of relying on a general article as implementation guidance.
Published articles
- AI Policy for Research Agencies: Now a Written Requirement
An AI policy for research agencies stopped being optional. What the revised standard asks for, what the code makes you declare, and what the log has to hold.
- AI Agent Evaluation Without an Answer Key
AI agent evaluation in research has no gold standard to score against. What the failure taxonomy shows, and how a judge from another maker is calibrated.
- Market Research Knowledge Base: Answers That Cite the Page
A market research knowledge base fails at retrieval, not at knowledge. What the measured numbers show, and why every citation has to come from a lookup.
- Open Weight Models in Market Research: The License Decides
Open weight models in market research keep confidential transcripts on your own servers. The measured gap against closed models, and what the license allows.
- Market Research Report Automation Starts Upstream
Market research report automation usually starts at the slide. Why the tabulation plan and the code frame are the real entry point, and what stays human.
- AI Adoption in Market Research: Past the Pilot
AI adoption in market research stalls after the pilot. What separates a pilot from production, what the public numbers show, and the gate a step has to cross...
- Market Research Dashboard: Built From the Decision
A market research dashboard is usually built from the variable list. What the BI adoption numbers show, and how writing the decisions first changes the scree...
- Research Community on WhatsApp: The Migration Tax
A research community on WhatsApp keeps people where they already are. What migrating an MROC costs, what the field literature found, and when a platform wins...
- Synthetic Respondents Concept Testing: The Fidelity Data
Synthetic respondents concept testing measured against human baselines: where the 70 and 85 percent fidelity numbers come from and what they let you decide.
- Enterprise AI Platform for Research Teams: 6 Gaps
What an enterprise AI platform for research teams does that a general chatbot cannot: training, shared agents, usage control, an indexed library, and roles.
- LLM Bias in Market Research: One Model, One Blind Spot
LLM bias in market research is systematic, not random. What one model gets wrong when it codes verbatims, and how a research team can actually catch it.
- Qualitative Coding With AI Without Losing the Evidence
Qualitative coding with AI shortens the first pass over interview transcripts. How open coding runs today, what it costs, and where review time returns.
- Survey Testing Before Fieldwork: Coverage Over One Click
Survey testing before fieldwork is usually one person clicking through once. What path coverage looks like instead, and what the untested path really costs.