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

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

Aside

Aside Computer Inc.

Freemium

A Chromium desktop browser with a built-in agent that signs in and completes real work across your logged-in sites.

Agentic Browsing: The agent operates your logged-in websites directly - clicking, typing and navigating - so tasks that need no public API still get done.
Local Memory: Browsing history is distilled into on-device memory files so the agent already knows which tools and accounts a recurring task involves.
Agent Password Manager: Credentials are autofilled into pages through hardware-backed encryption and Secure Enclave storage, never handed to the model.
Human Approval Gates: Sensitive steps such as payments, posts and outbound messages pause for your confirmation before the agent proceeds.
Access Audit Log: Every credential use and scoped permission grant is recorded so you can see exactly what the agent touched and when.
Routines: Scheduled recurring tasks, such as a 9am daily briefing, run on their own and drop results back into the browser.
Bring Your Own Model: Connect an existing ChatGPT or Claude subscription or your own API key rather than paying twice for inference.
Sandboxed Execution: Filesystem and network access are isolated with guardrails so agent runs cannot reach beyond what the task needs.

Operations Backfill: Push the same record update through several internal dashboards that have no shared API.
Recruiting Prep: Reopen a candidate profile viewed yesterday and assemble interview notes from the sites already visited.
Inbox and Comment Triage: Draft replies, follow-ups and comment responses across email and social accounts under review.
Daily Briefing: Schedule a routine that gathers overnight metrics and trending topics into one morning summary.
Sales Research: Work through prospect sites and CRM screens to collect context before an outreach sequence.
Spreadsheet and Document Work: Have the agent edit local files and web spreadsheets as part of a longer task.

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.