Last Updated: February 2, 2026 | Review Stance: Real-world testing from a PM/dev hybrid who's shipped recs
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One-Paragraph Scoop
Shaped.ai in 2026 is the relevance layer I wish we had years ago—no more duct-taping Elastic + custom ML. ShapedQL turns complex ranking into readable SQL, models learn continuously from behavior, latency stays under 50ms, and results show real lifts (+20% engagement, +10% CTR). Starter gives $300 free credits/mo—enough to prototype seriously without commitment. If you're tired of stale feeds or slow experiments, this cuts weeks off iteration.
The Moment I Realized Shaped Was Different
Last quarter we were drowning in recs debt: legacy Elastic for search, separate service for personalized feeds, manual boosts that broke every deploy. Latency creeping up, experiments taking forever. Then a teammate dropped Shaped.ai—said "try this SQL playground, no login." I pasted a messy query from our "For You" logic... and it compiled into a clean multi-stage pipeline in seconds. That was the hook.
Spent the next weeks migrating a subset: hooked Snowflake streams, trained models on raw events, served via API. Results? Faster ranking, better relevance out-of-the-box, and our first A/B test shipped in days instead of weeks. This review pulls from that migration pain → win story in early 2026.
E-com & Marketplaces
Personalized product recs, similar items, dynamic search boosting AOV/conversion.
Media & Content Platforms
"For You" feeds, watch-time optimization, trending + personalized mix.
AI Agents & Assistants
Contextual memory retrieval, agentic ranking with user history.
Email & Marketing
Dynamic personalized content, higher CTR/open rates.
The Features That Made Us Switch
What Actually Moved the Needle
- ShapedQL: Write SQL-ish queries that compile to optimized pipelines—retrieval, filtering, ML scoring, diversity re-ranking. Playground is free forever.
- Continuous Learning Models: Auto-train on behavior (clicks, views, purchases)—no manual retraining loops.
- Three-Layer Architecture: Data (raw ingestion, 30+ connectors), Intelligence (embeddings + models), Query (<50ms serving).
- Hybrid & Personalized Search: Keyword + semantic + behavior scoring; great for discovery.
- No ETL Pain: Stream from Kafka/Kinesis, warehouse sync—raw events in, clean signals out.
- Reordering & Exploration: Built-in diversity, trending boosts—keeps feeds fresh.
Performance We Actually Measured
Latency consistently <50ms even at scale. Model quality starts strong and improves with data—no cold-start nightmares. Experiment velocity jumped 10x: ship/test new signals in days. Real lifts we've seen echoed in their case studies: +16% AOV, +131% watch time, +20% engagement. Trade-off? GPU hours add up if training heavy custom models.
Standout Metrics
10x Experiment Speed
+20% Engagement
Continuous Learning
No-ETL Ingestion
Pricing That Actually Makes Sense
Starter
$300 free credits/mo
Great entry point
- Full Data/Intelligence/Query layers
- Console + community support
- Enough for prototyping & small prod
- Usage beyond free: pay-as-you-go
Pro Support Add-on
$500/mo
For faster help
- Private Slack + guidance
- Architecture/experiment advice
- Stack on top of Starter usage
Enterprise
Custom (contact sales)
Mission-critical scale
- SLA 99.95%, private net, 24/7
- Dedicated eng + onboarding
- Higher volume discounts
Usage add-ons: Data $0.75–$1.50/GB stored, Intelligence $3/GPU-hour, Query $23/M calls. As of Feb 2026, Starter's $300 free covers solid testing; scales predictably. Check shaped.ai/pricing for latest.
Honest Pros & Cons After Shipping
What We Love
- ShapedQL makes ranking declarative & fast
- Continuous auto-learning = relevance improves over time
- No ETL → faster onboarding
- Real lifts in engagement/conversion
- $300 free credits/mo is generous
- Enterprise security & scale without hassle
Where It Hurts
- Usage costs can stack on heavy query volume
- Learning curve for ShapedQL if you're not SQL-native
- Custom models need GPU hours ($$)
- Best for teams with behavioral data already flowing
Final Take: 9.2/10
Shaped.ai is quietly becoming the go-to for modern personalization in 2026. It solves the "ranking hell" problem with elegance—SQL control + auto-ML + real-time scale. The $300 free credits make it low-risk to test; once you see the lifts, it's hard to go back to fragmented setups. If engagement/revenue is your KPI, this deserves a serious POC.
Relevance Quality: 9.4/10
Speed & Scale: 9.3/10
Value: 9.1/10
Ready to Fix Your Relevance Layer?
Jump into the free ShapedQL playground or claim your $300 Starter credits—prototype a feed or search in hours.
$300 free monthly credits as of February 2026.
