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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Coral is a developer-focused data access platform that lets teams query different tools and systems with SQL instead of writing custom connectors. It converts APIs, databases, files, and software platforms into readonly schemas that agents and humans can inspect, join, and analyze. Users can connect sources such as GitHub, GitLab, Slack, Linear, Datadog, Sentry, OpenTelemetry, Intercom, Stripe, and incident management tools. Once connected, Coral makes those sources available as tables, allowing cross-system questions to be answered through standard SQL. The platform is designed for AI agent workloads, giving coding agents and operational assistants access to structured context without unsafe write access. Coral works through the command line and over MCP, so multiple agents can share one runtime. It includes query pushdown, caching, pagination handling, schema hints, recommended joins, and relationship learning based on usage patterns. These capabilities help reduce expensive tool loops and improve the quality of agent-generated answers. Coral gives teams a practical way to make scattered operational data accessible, queryable, and useful for engineering, SRE, security, support, and internal operations.

Description

Engram is an advanced, fully managed service designed to enhance memory and context for AI agents, enabling them to retain, learn, and evolve effectively over time. Rather than accumulating an unmanageable collection of unstructured conversations and events, it meticulously transforms chaotic interaction data into well-organized, lasting, and adaptive memories. Applications can seamlessly transmit raw text, entire dialogues, or pre-processed facts via a REST API or Python SDK with no need for prior formatting. Engram then operates asynchronous processes that extract pertinent information, streamline it by removing duplicates and aligning it with existing knowledge, resulting in a refined memory state that does not interfere with the main operations of the application. It addresses inconsistencies, adjusts to evolving preferences and changing information over time, ensuring that the context remains both relevant and efficient. Additionally, agents have the capability to access prioritized memories instantly through vector similarity, BM25 keyword searches, or a combination of retrieval methods, thereby minimizing the necessity to resend complete conversation logs. This approach significantly enhances the efficiency and effectiveness of interactions, making AI agents more responsive and capable of understanding user needs.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Claude Code
Datadog
GitHub
Linear
Model Context Protocol (MCP)
OpenAI Codex
PagerDuty
Python
Sentry
Slack
Stripe
Weaviate

Integrations

Claude Code
Datadog
GitHub
Linear
Model Context Protocol (MCP)
OpenAI Codex
PagerDuty
Python
Sentry
Slack
Stripe
Weaviate

Pricing Details

$249/month
Free Trial
Free Version

Pricing Details

$45 per month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Coral

Founded

2024

Country

United Kingdom

Website

withcoral.com

Vendor Details

Company Name

Weaviate

Founded

2019

Country

The Netherlands

Website

weaviate.io/product/engram

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