Welcome HN! Here's a promo code for a free month of Tamber FIFO

Your app, powered by machine learning

Deploy your own Google-scale recommendation features in minutes. Optimize your user experience on the fly with the next generation of Artificial Intelligence.

Give users what they like

Engage users the second they land with personalized content, optimized to make sure they see something they will click on right away.

$ curl https://api.tamber.com/v1/discover/recommended \
	-u Mu6DUPXdDYe98cv5JIfX: \
	-d user=user_rlox8k927z7p \
	-d number=10

items = Tamber::Discover.recommended(
  :user => 'user_rlox8k927z7p',
  :number => 10
)

JSONObject resp = tamber.discover.next(new JSONObject()
        .put("user", "user_rlox8k927z7p")
        .put("number", 10)
    );

items = tamber.Discover.recommended(
    user='user_rlox8k927z7p',
    number=10
)

const items = await tamber.discover.recommended({
	user: "user_rlox8k927z7p",
	number: 10
});

items, info, err := discover.Recommended(
	&tamber.DiscoverRecommendedParams{
		User: tamber.IdString("user_rlox8k927z7p"),
		Number: tamber.Int(10)
	}
)

TMBDiscoverParams *params = [TMBDiscoverParams discoverRecommended:[NSNumber numberWithInt:10]];
[[Tamber client] discoverRecommended:params responseCompletion:^(TMBDiscoverResponse *object, NSHTTPURLResponse *response, NSString *errorMessage) {
    if(errorMessage){
        // Handle error
    } else {
        object.discoveries // Array of recommendations
    }
}];

$ curl https://api.tamber.com/v1/discover/recommended \
	-u Mu6DUPXdDYe98cv5JIfX: \
	-d user=user_rlox8k927z7p \
	-d item=item_83jx4c57r2ru

items = Tamber::Discover.next(
  :user => '583480',
  :item => '90674'
)

JSONObject resp = tamber.discover.next(new JSONObject()
        .put("user", "user_rlox8k927z7p")
        .put("item", "item_83jx4c57r2ru")
    );

items = tamber.Discover.next(
    user='user_rlox8k927z7p'.
    item='item_83jx4c57r2ru'
)

const items = await tamber.discover.next({
	user: "user_rlox8k927z7p",
	item: "item_83jx4c57r2ru"
});

items, info, err := discover.Next(&tamber.DiscoverNextParams{
	User: tamber.IdString("user_rlox8k927z7p"),
	Item: tamber.IdString("item_83jx4c57r2ru")
})

TMBDiscoverParams *params = [TMBDiscoverParams discoverNext:@"90674"]];
[[Tamber client] discoverNext:params responseCompletion:^(TMBDiscoverResponse *object, NSHTTPURLResponse *response, NSString *errorMessage) {
    if(errorMessage){
        // Handle error
    } else {
        object.discoveries // Array of recommendations
    }
}];

Create a path of discovery

Create a path of discovery that keeps users clicking. Tamber’s next-model learns on sequences of user actions to predict what users will most want to interact with next.

Reel them back in

Keep users coming back by sending recommendations via email or push notification. Tamber’s push-model ensures that content is always relevant, and your messages always delightful.

Integration easy as π

Track user events just like you do for analytics, or use our Segment integration for a codeless install.

Checkout our SDKs on Github

Node.js
Ruby
Python
Go
Objective-C
Java
curl

$ curl https://api.tamber.com/v1/discover/recommended \
	-u :SbWYPBNdARfIDa0IIO9L \
	-d user=user_rlox8k927z7p

require 'tamber'
Tamber.engine_key = 'SbWYPBNdARfIDa0IIO9L'

Tamber::Discover.recommended(
  :user => 'user_rlox8k927z7p'
)

Tamber tamber = new Tamber("Mu6DUPXdDYe98cv5JIfX", "SbWYPBNdARfIDa0IIO9L");

HashMap<String, Object> discoverParams = new HashMap<String, Object>();
discoverParams.put("user", "user_rlox8k927z7p");

JSONObject resp = new JSONObject();
try {
    resp = tamber.discover.recommended(discoverParams);
} catch (TamberException e) {
    System.out.println(String.format("%s=%s", e.getClass().getName(), e.getMessage()));
}

import tamber

tamber.engine_key = 'SbWYPBNdARfIDa0IIO9L'
tamber.Discover.recommended(
    user='user_rlox8k927z7p'
)

var tamber = require('tamber')('Mu6DUPXdDYe98cv5JIfX');

const items = await tamber.discover.recommended({
	user: "user_rlox8k927z7p"
});

package main

import (
	tamber "github.com/tamber/tamber-go"
	"github.com/tamber/tamber-go/discover"
)

func main() {
	tamber.DefaultEngineKey = "SbWYPBNdARfIDa0IIO9L"

	d, info, err := discover.Recommended(
		&tamber.DiscoverRecommendedParams{
			User: tamber.IdString("user_rlox8k927z7p"),
		}
	)
}

@import Tamber;

[Tamber setPublishableProjectKey:@"your_project_key"];
[Tamber setUser:@"user_rlox8k927z7p"];

TMBDiscoverParams *params = [TMBDiscoverParams discoverRecommended:[NSNumber numberWithInt:8]];
[[Tamber client] discoverRecommended:params responseCompletion:^(TMBDiscoverResponse *object, NSHTTPURLResponse *response, NSString *errorMessage) {
    if(errorMessage){
        // Handle error
    } else {
        object.discoveries // Array of recommendations
    }
}];

[
  {
    "item": "item_83jx4c57r2ru",
    "score": 0.94321,
    "item_created": 1481167989
  },
  ...up to 200 items per page...
]

ChefsFeed is a complicated platform from a data perspective, with videos, articles, restaurants, chef profiles, events, and more all surfaced across our website and apps. Tamber handles all of these content types seamlessly. It just works.

Tom Bash
VP of Product

Our Tamber-powered Discover Daily feature immediately became our highest converting feed, with a 4x higher click-through than the next best. Our users love their recommendations, and now it's the first thing they see when they open the app.

David Oates
Co-Founder & CEO

Tamber enabled us to transform our app into a smart, optimized shopping experience. We love using Tamber, and our users love the results.

Pradeep Elankumaran
Co-Founder & CEO

Pay as you grow

Plans scale with your user growth. No setup charges, no hidden fees, just track everything.

Free 2-week trial

Only pay when it works. In the first week we establish a performance baseline, and then we surpass it.

Dead simple integration

We are maniacal about our ease-of-use. We pair-program with your devs, and will even hand code integrations when it’s helpful.

Recommend like Google, Amazon and Facebook.