Indellia is sentiment analysis software for product reviews specifically. Aspect-based scoring at SKU level. Deterministic AI heritage from NEC Labs. indelliaGPT™ answers cite the underlying reviews — no hallucinated quotes.
The short answer
Sentiment analysis software classifies feedback into positive, negative, or neutral signal — and increasingly does so at the aspect level (sentiment per feature or theme, not just per review). Indellia is sentiment analysis software tuned for product reviews on retail channels. Aspect-based sentiment per SKU. Deterministic AI architecture, with indelliaGPT™ returning cited summaries instead of hallucinated quotes.
Old-school sentiment analysis returns "this review is 0.7 positive." Useful for trend lines; useless for action. A 4-star Amazon review can be 90% glowing about build quality and 90% scathing about battery life. The aggregate score lies.
Aspect-based sentiment analysis (ABSA) returns sentiment per aspect — battery, build, setup, durability, value. The right unit for product feedback. Read more in the aspect-based sentiment analysis definition.
Modern sentiment analysis software for consumer brands also has to handle:
Indellia's foundational NLP traces back to NEC Labs research on product feedback specifically — not adapted from chatbot text or social media sentiment. The aspect detection is tuned for the language consumer brands actually see in reviews.
Sentiment is scored per aspect (battery, build, setup, value, durability) extracted by the Theme Agent. Aggregate sentiment is available; aspect-level is the default. The right unit of analysis for product feedback.
indelliaGPT™ returns sentiment summaries with citations to the underlying reviews. No invented quotes. No fabricated numbers. The architecture is explicitly positioned against LLM hallucination.
Sentiment per SKU per retailer per time period. The Anomaly Agent watches for sentiment deviations and alerts when reality diverges from forecast — useful for catching a launch issue or a firmware-driven shift.
Amazon, Walmart, Best Buy, Costco, Lowe's, Target, Home Depot, Bazaarvoice retailer pages.
Zendesk, Intercom, Freshdesk, Gorgias, Gladly, Kustomer, Front.
Loop, Narvar, AfterShip. Typeform, SurveyMonkey, Qualtrics. Grain, Gong, Twilio.
Snowflake (read + Mid-Market pushback). Shopify. Segment.
Indellia's sentiment models are tuned for product reviews and consumer-brand feedback. If your use case is sentiment on news articles, social media broadly, or open-domain text outside the product-review context, a general-purpose NLP API (Google Cloud Natural Language, AWS Comprehend, Azure Cognitive Services) will fit better. Indellia would still work — but you'd be paying for retail-specific tuning you don't use.
Sentiment analysis software classifies feedback text into positive, negative, or neutral signal. In 2026 the meaningful version is aspect-based sentiment analysis: sentiment scored per aspect (battery, build, setup, value) extracted from the text, not aggregated to a single per-review score. Aggregate scores hide product-specific signal that aspect-level scoring surfaces.
Sentiment accuracy in product-review NLP varies by category and language style; we don't publish a single accuracy number because the right comparison is against your own corpus. The deterministic-AI architecture and the NEC Labs heritage on product feedback specifically tend to outperform generic sentiment APIs in our customer evaluations. The free trial is the practical test — run Indellia against your own SKUs and see.
Yes — new reviews are scored as they're ingested, typically within the first ingestion cycle (minutes to hours depending on the channel). Aspect detection runs alongside, so the per-aspect sentiment view updates with every new review.
Yes. The Theme Agent generates an automatic aspect taxonomy from your feedback, and you can layer your own aspect categorization on top. Most consumer brands run with the auto-generated aspects for the first month, then pin and merge to match the way the team talks about the product internally.
indelliaGPT™ uses deterministic retrieval to find the source reviews relevant to your sentiment question, then summarizes them with citations to each source review. The language model does not invent quotes or sentiment labels — it works only from records that exist in your corpus. See the LLM hallucination definition for the architecture rationale.
Indellia's AI agents answer with citations from real customer feedback across Amazon, Walmart, Best Buy, and 20+ retail channels.
Start the free trial; aspect-based sentiment per SKU populates within hours.