sourcerykit logo
sourcerykit
★ 21
vs
platform logo
platform
★ 15

sourcerykit vs platform

sourcerykit: SourceryKit, also known as Provably SDK, is a Python library that integrates a deterministic evaluation layer into any Python agent. It records outbound HTTP calls, evaluates claims against trusted records, and enforces endpoint policies to ensure agents operate within defined boundaries.; platform: SidClaw intercepts AI agent tool calls, checks them against defined policies, and holds risky actions for human review. It prevents agents from executing unauthorized or high-risk operations, ensuring secure and compliant AI deployments.

01

TL;DR

sourcerykit logo
sourcerykitSecurity & Safety · ★ 21

Ensuring LLM agents adhere to pre-defined security policies and trusted endpoints.

platform logo
platformSecurity & Safety · ★ 15

Customer Support Agent (Financial Services): Governing email sending and other sensitive operations by AI agents in financial customer support.

02

Side-by-Side Comparison

Field
sourcerykit logosourcerykit
platform logoplatform
Category
Security & Safety
Security & Safety
Stars
★ 21
★ 15
License
NOASSERTION
Apache-2.0
Install Command
git clone [email protected]:ProvablyAI/provably-python-sdk.git && pip install -e ./provably-python-sdk
git clone https://github.com/sidclawhq/platform && cd platform/packages/sidclaw-demo && node cli.mjs
Updated
3d ago
4d ago
Open Source
Yes
Yes
Tags
Python SDK, LLM Agent, Verifiable Guardrails
AI Agent Governance, Tool Call Control, Security
03

Features

sourcerykit logosourcerykit
01Intercept and Police outbound HTTP calls against trusted endpoints.
02Capture and Store all HTTP requests and responses into a Postgres database.
03Evaluate agent claims against proven indexed values using deterministic comparisons.
04Seamless integration with major LLM frameworks and SDKs like OpenAI, LangChain, and LlamaIndex.
platform logoplatform
01Policy engine: allow / approval_required / deny with priority ordering and classification hierarchy.
02Approval workflow: context-rich cards with agent reasoning, risk classification, and separation of duties.
03Audit trails: correlated traces with integrity hash chains (tamper-proof).
04Fast setup: `npx create-sidclaw-app` scaffolds a working governed agent in seconds.
05Framework-agnostic: Compatible with LangChain, OpenAI, Claude Agent SDK, and many more, or plain functions.
04

Use Cases

sourcerykit logosourcerykit
↳Ensuring LLM agents adhere to pre-defined security policies and trusted endpoints.
↳Verifying the accuracy of claims made by AI agents based on their external interactions.
↳Building auditable AI systems where every external call and agent claim is recorded and verifiable.
↳Implementing verifiable guardrails for agents to prevent unauthorized access or data manipulation.
platform logoplatform
↳Customer Support Agent (Financial Services): Governing email sending and other sensitive operations by AI agents in financial customer support.
↳Infrastructure Automation (DevOps): Enforcing human approval for high-risk deployments or scaling operations performed by AI agents in DevOps.
↳Clinical Decision Support (Healthcare): Allowing physicians to review and approve AI assistant recommendations for lab orders, while blocking restricted actions like medication prescribing.
FAQ

FAQ

What is the difference between sourcerykit and platform?
Both sourcerykit and platform are in the Security & Safety category. sourcerykit has 21 stars, while platform has 15 stars.
Which is better, sourcerykit or platform?
The best choice depends on your use case. Choose sourcerykit if Ensuring LLM agents adhere to pre-defined security policies and trusted endpoints., and platform if Customer Support Agent (Financial Services): Governing email sending and other sensitive operations by AI agents in financial customer support..
Is sourcerykit free or open source?
Yes, sourcerykit is open source on GitHub (NOASSERTION).
Is platform free or open source?
Yes, platform is open source on GitHub (Apache-2.0).
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