Tamber
Recommendation engines for developers, easy as pi
About Tamber
Tamber is a hosted recommendation engine API that lets developers add personalized recommendations to any app in minutes. By streaming user-item interactions in real time, Tamber's machine learning models generate highly accurate recommendations for content, products, and more — ideal for developers and product teams who want Google-scale personalization without building ML infrastructure.
Pros & Cons
Pros
- Extremely simple API design makes integration possible in minutes with minimal code
- Generous free tier with 5,000 MAU allows startups to validate recommendations before committing
- Multi-language SDK support covers nearly all major backend and mobile platforms
- Real-time event streaming ensures recommendations stay current as user behavior changes
- Segment integration enables codeless setup for teams already using Twilio Segment
Cons
- Acquired by Beek.io in 2022 — long-term platform availability and active development uncertain
- Requires 1-2 weeks of event data collection before recommendations become useful
- Steep price jump from Startup ($100/mo) to Business ($4,250/mo) with limited mid-range options
- No built-in dashboard UI for non-technical users to configure or review recommendations
- Limited community and ecosystem compared to larger players like AWS Personalize or Algolia Recommend
Key Features
Personalized Recommendations
Generate highly accurate personalized content, product, and media recommendations using ML models trained on user behavior
Real-Time Event Streaming
Track user interactions like clicks, purchases, and views as they happen to continuously improve recommendation quality
Multiple Discovery Models
Choose from Recommended, Next, Weekly, Daily, Popular, Hot, and Trends endpoints to surface content in different contexts
Multi-Language SDKs
Native client libraries for Node.js, Python, Ruby, Go, Java, iOS (Objective-C), and JavaScript for quick integration
Segment Integration
Connect with Twilio Segment for codeless event streaming without writing custom tracking code
Batch Event Processing
Upload up to 1,000 events per API call for efficient historical data import and high-volume tracking
Filtering & Metadata
Filter recommendations by item properties, tags, and custom metadata with logical operators for precise targeting
A/B Testing & Context Tracking
Tag events with page or section context to run experiments and measure recommendation performance across different placements
User Merge & Identity Resolution
Merge anonymous and authenticated user profiles to maintain continuous recommendation quality across sessions
Meta Recommendations
Discover trending properties and tags per user to surface higher-level preference insights beyond individual items
Pricing
- Up to 5,000 monthly active users
- 2 recommendation engines
- Event tracking
- All SDK access
- REST API access
- Forever free
- Up to 10,000 monthly active users
- 2 recommendation engines
- 14-day free trial
- Overage: +$150 per 5,000 MAU
- +35% per additional engine
- Up to 250,000 monthly active users
- 4 recommendation engines
- Priority support
- Overage: +$125 per 5,000 MAU
- +30% per additional engine
- Custom MAU limits
- Push Notifications
- Location Services
- OptiStart onboarding
- A/B Testing
- Dedicated support