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Comparison · Analytics

PostHog vs Hex

Side-by-side trajectory, velocity, and editorial themes.

PostHog logo
PostHog
ANALYTICS
5.0

PostHog is wiring itself into the MCP ecosystem while shoring up mobile-SDK feature parity.

◆ Current state

PostHog continues its weekly grind, but the May releases cluster around two themes: an MCP toolchain (alerts to Slack and webhooks, SDK Doctor, mode selection via header) and LLM analytics BYOK providers (Together AI, Azure OpenAI). At the same time the mobile teams are filling in iOS and Android session-replay controls, rage-click detection, and survey delays that previously only the web SDK had.

◆ Where it's heading

The shape of PostHog's surface keeps widening rather than deepening: more LLM-vendor coverage in the analytics product, more MCP-tooling so AI agents can read and act on PostHog data, more parity across SDKs. Less obvious is which surface becomes the headliner; right now Conversations, Logs, Experiments, and Client Libraries are all shipping into a single weekly digest with comparable weight.

◆ Prediction

Expect MCP integration to keep expanding from peripheral utilities into the core insights and alerting paths, with PostHog positioning itself as the analytics endpoint AI agents read from when reasoning about product usage. Mobile SDK parity work should compress in the next month or two as the gap with the web SDK closes.

H
Hex
ANALYTICS
6.3

Hex is rebuilding itself as an agent that turns prompts into data apps.

◆ Current state

Hex has pivoted into agentic data analytics: an AI agent that builds analyses, dashboards, and now whole apps from prompts. Across this window it has widened the agent's context (repos, user memory, semantic models), its reach (MCP client, availability inside Codex), and its output surface (generative data apps).

◆ Where it's heading

The throughline is an agent that ingests broad context and acts across external tools rather than staying boxed in a notebook. Generative Data Apps plus MCP-client connectivity point at Hex wanting to be the agentic layer over a company's data stack, not just its analysis canvas.

◆ Prediction

Expect deeper agent autonomy and more model/tool options next, building on the model picker, web search, and MCP work visible here. More app-template or embedding paths are the likely follow-through to Generative Data Apps.

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