Hexis vs Playad: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Hexis and Playad — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Hexis

Bevelites GmbH

Freemium

Open-source git-backed control plane for enterprise AI agents — context, skills, tools and permissions as files in your own repo, served over MCP.

Git-backed source of truth: Context, skills, tools, permissions, and agent identities live as Markdown/YAML files in your own repository — reviewed, branched, and diffed like any other code.
Typed knowledge with provenance: Every fact is a typed node with source, owner, and last verification date, compiled into a graph you can traverse, mass-update, and dashboard.
Markdown skills, not prompt fragments: Procedures live as readable Markdown files that domain owners can review, instead of prompt snippets buried in a vendor config.
Tool manifests with vaulted secrets: Declare each tool once, hold secrets in a vault, and set file-level access rules that say which agent may read which file and call which endpoint.
Per-agent identity: Each agent is a named actor with its own credentials and scope — no shared service accounts, and every action is attributable to a specific agent.
Any runtime via MCP or UTCP: Serves the same governed surface to Claude Code, Cursor, ChatGPT, opencode, background agents, in-platform agents, and self-hosted models.
Open-source Apache-friendly release: Hexis is the OSS core; Bevel (paid) adds hosted services, integrations, and enterprise support on top.

Enterprises running AI agents across multiple vendors (Claude, Cursor, ChatGPT) who want context and skills defined once in their own infrastructure instead of re-uploaded per vendor.
Procurement, GTM, and RFI teams building specialised agents (e.g., tender desks, campaign agents) on top of a shared reusable knowledge layer with provenance.
Platform teams that need per-agent identities and file-level access controls so every tool call is attributable and destructive endpoints are gated by review.
Companies wary of vendor lock-in who want a portable spec (MCP/UTCP) so they can switch agent runtimes without rebuilding context, skills, and tool wiring.
Engineering leaders who want the AI 'operating manual' reviewed in git diffs and change requests instead of edited inside a black-box vendor console.
Open-source-first teams evaluating a control plane locally with Hexis before committing to Bevel's hosted platform for larger deployments.

GIGR, Inc

Freemium

AI marketing agent that creates, launches, tests and optimizes Meta, Google and TikTok ad campaigns on autopilot from a single chat.

Autopilot Campaign Management: Plans, launches and updates campaigns and reallocates budget automatically.
Hypothesis-Driven Testing: Forms hypotheses, isolates variables and runs A/B tests to find winning creatives.
Chat to Creative: Analyzes competitors and generates ad variations from a chat interface.
Competitor Ad Tracker: Monitors top-performing ads, hooks and trending formats in your category.
AI Video and Image Ads: Generates UGC-style videos, product shots and image ads with an AI editor.
Automated Reporting: Daily performance reports and weekly creative refreshes delivered to Slack.
Scheduler: Schedules ads, test variations and recurring experiments.
Multi-Platform Support: Works with Meta Ads, Google Ads and TikTok Ads.

A small e-commerce team replaces hours of weekly ad production with automated creative generation and testing.
A mobile game studio runs user-acquisition campaigns across platforms with a small marketing team.
A performance marketer clones competitor ad styles and adapts them to their own brand.
A founder with no marketing hire drops in a website URL and gets campaigns launched.
A marketing lead receives daily ROAS reports in Slack and approves budget shifts.
An agency scales creative testing across several brands using higher-tier plans.