Make alternative: Backbuild automation and Virtual Workers

Backbuild automation and Virtual Workers vs Make: feature by feature

Make prices, plans, and capabilities below are from Make pages, observed 2026-07-20 and subject to change. The highlighted column is Backbuild.

A cross means the tool does not offer the feature today. Make prices, plans, and capabilities are quoted from the Make pricing, product, integrations, and security pages, observed 2026-07-20. Backbuild capabilities are cited to the workflows and automations documentation, the Virtual Workers docs, the Secrets vault, SSO and SCIM, MCP, and API reference pages, and the pricing page. The Chat, Meetings, Diagrams, video, audio, and music editor rows and the unattended orchestrated runtime are marked at the status Backbuild ships them at today, not asserted as complete.

A visual scenario across connected apps, or an AI worker on a real computer

Make is a strong, mature automation platform. Its strength is building multi-step scenarios on a drag-and-drop node-graph canvas that connects more than three thousand pre-built app integrations and routes, filters, iterates, and transforms data between them, quickly and predictably, often with no code and no AI at all. For a visual data flow between popular SaaS apps, that is exactly the right tool, and its builder, its connector catalog, and its data-mapping depth are genuine advantages. Backbuild automates a different way. A Backbuild automation rule fires on a workspace event or a timer and dispatches an action, and its most distinctive action hands the task to an autonomous AI Virtual Worker that operates a full Linux desktop, a browser, and a terminal, so it can reason through a multi-step task and drive an application the way a person would, including an application that has no API. It acts under credentials your organization governs in an encrypted vault the model never reads in plaintext, inside per-organization roles and a tamper-evident audit trail on every plan, on the AI model of your choice. Where the work is a deterministic visual flow across mainstream APIs, Make is the faster fit. Where it needs to operate real systems, reach no-API apps, and run under governed credentials, Backbuild is built for it.

Two mechanisms for automating work

The clearest way to see the difference is to follow one automation through each product. In Make a trigger fires in a connected app, and Make routes the data through the scenario modules, calling the APIs of the other connected apps to filter, transform, and act, step by step, across its catalog. In Backbuild a rule fires on a workspace event or a timer and dispatches an AI worker onto an isolated container, where the worker operates a real desktop, a browser, and a terminal to do the task, pulling any credential it needs from the vault without the plaintext ever entering the model. One reaches apps through their APIs on a visual canvas; the other operates the systems directly.

How an automation signs in without the model seeing the password

Make authenticates through connections: when you connect an app, Make stores an authenticated OAuth grant or an API key in the connection configuration and uses it to call that app on your behalf. That is convenient and it works across the whole connector catalog, and the stored connection is what a scenario acts through. Backbuild handles credentials so that no human has to type them and the model still never sees them. Secrets live in your organization vault, an encrypted, zero-knowledge, post-quantum vault, and the model that drives a worker never receives a plaintext value, because no tool returns one. When a worker needs to sign in, the vault hands back an opaque, single-use reference, not the secret. A trusted path substitutes the real value at the moment of use, on a loopback the model cannot read, so the credential reaches the target app while staying out of the model context, its results, and the logs. That is the difference a security reviewer cares about: the automation acts with the login, unattended, without the plaintext ever being present in the automation or the model.

How every automation action stays governed

Autonomy is only safe when it is bounded, so a Backbuild Virtual Worker runs each action through the same set of controls. The run executes as a governed finite-state-machine skill with deterministic, reviewable states rather than a free-form plan. Before an action takes effect it passes an autonomy dial and a non-overridable approval floor, so sending external email and pushing code always require a person no matter how autonomous the run is set to be. The worker holds a scoped, revocable delegated token behind a default-deny capability gate that excludes secrets, roles, billing, and administration. And every action is attributed and written to a tamper-evident audit trail on every plan. Make answers with manual scenario controls and places its audit logs and team roles on Teams and up, where Backbuild provides roles and audit on every plan.

Where Make wins today

Make is a market leader for good reasons, and several of its strengths are things Backbuild does not match today. An honest evaluation names them plainly.

Common Make frustrations and how Backbuild addresses them

Which tool wins, by use case

Security and compliance evaluation

Because an automation platform logs in and acts on real systems, a sharp evaluation of this category is a security one, and it turns on a short list of criteria: where credentials live and who can read them, how tightly a run is scoped and how fast it can be stopped, whether governance and audit are present or gated to a higher tier, and the vendor own posture and attestations. Both products should be measured against those, not against a feature count.

On credentials, the two take different designs. Make stores an authenticated connection, an OAuth grant or an API key, in the connection configuration and uses it to act on the connected app. That is standard for an integration platform and it works across the whole catalog, and the stored grant is what a scenario acts through. Backbuild keeps credentials in an encrypted, zero-knowledge vault the model never reads in plaintext: no tool returns a plaintext value, and a trusted path substitutes the real credential at the point of use, so a worker signs in unattended without the secret ever being present in the automation or the model. For a reviewer who treats every automation as a privileged non-human identity, that difference is the center of the evaluation.

On blast radius and control, Backbuild runs each worker session in an isolated, disposable container under a scoped, signed delegated token that is least-privilege, time-limited, and checked against a server-side revocation list on every use, so tearing down a session is a real kill switch, and the code a worker runs is held to a default-deny allowlist that excludes secrets, roles, billing, and administration. A non-overridable approval floor keeps two actions, sending external email and pushing code, always requiring a person. The operation stream itself is post-quantum encrypted. Backbuild also provides per-organization roles, single sign-on, SCIM 2.0 provisioning, and tamper-evident audit on every plan, where Make places team roles and audit logs on Teams, and company SSO on Enterprise.

On vendor posture the honest picture runs both ways. Make carries independent compliance attestations including SOC 2 Type II, SOC 3, ISO 27001, and GDPR adherence, with AES-256 encryption at rest and TLS 1.2 and 1.3 in transit, and a long operating history, which Backbuild does not yet match, and that is a genuine advantage for a buyer who requires an attested, established vendor now. At the same time, Backbuild offers a stronger structural posture for credentialed automation: a governed vault, per-session isolation, a revocable token, a default-deny gate, and governance on every plan rather than only on the top tiers. The bottom line for a security evaluation is that Make leads on independent attestations and operating maturity, while Backbuild leads on the credential design and the control set for autonomous work under organization governance.

The economics for a finance buyer

A finance evaluation of an automation platform is about total, predictable cost rather than a sticker price. The criteria are the entry cost, how the meter behaves as usage grows, and whether the spend can be forecast month to month across a team.

On entry cost, both have a free tier, and Make free plan is a well-known on-ramp: 1,000 credits a month and two active scenarios, with Core from about 12 US dollars a month for 10,000 credits, Pro from about 21, Teams from about 38, and Enterprise custom, and roughly fifteen percent off on annual billing. The dynamic a finance buyer should model is the credit meter: most actions consume one credit, but AI modules can draw a variable number of credits depending on the tokens, files, or pages they process, so cost scales with automation and AI volume and can be harder to forecast for a busy, AI-heavy workload. Make per-credit pricing is competitive and a genuine strength for straightforward scenarios. Backbuild folds automation work into one universal usage-credit pool with idle time free, includes automation rules and Virtual Workers on a free plan, and lets a team bring its own AI provider and model so inference runs at the provider rate rather than a bundled markup.

The tradeoff a finance buyer should weigh is that Backbuild is usage-metered too: heavy worker work and larger container sizes draw more credits, so an always-busy workload is not free, and a team should size its credit budget against real usage rather than the free entry point. Against that, Make pricing is a familiar per-credit line item that many teams already understand, and its entry tiers are inexpensive. The bottom line: Backbuild is the single-pool, model-portable cost structure with governance included and idle time free, while Make is a mature, competitively priced plan whose credit meter rewards simple scenarios and grows with multi-step and AI volume.

Rolling it out across a team

For the person putting an automation platform into a real team process, the evaluation is about time-to-first-result, how the tool behaves when a run goes wrong, and whether governance scales with the team without forcing a top-tier upgrade. These are operational criteria, and the two products lead on different ones.

On time-to-first-result, Make is usually ahead for a self-contained app-to-app task: a template and a couple of connected apps stand up a working scenario quickly on the canvas, and that speed is real and worth crediting. Backbuild trades some of that immediacy for surface and governance, because you direct an AI worker with prompts and governed skills on a real computer, but it makes a multi-step job states deterministic and reviewable and every action attributed and audited from the first run rather than only on a paid plan.

On governance at scale, the difference is where the controls live. Make gates team roles and audit logs to Teams, and company SSO to Enterprise, so a growing team reaches for a paid upgrade to get them. Backbuild provides single sign-on and SCIM 2.0 provisioning and per-organization roles, data isolation, and a tamper-evident audit trail on every plan, including Free, and each worker session runs under a revocable token that makes a run that goes wrong visible and stoppable. The honest counterpoint is that a governed AI-worker approach on a real computer asks more of the person setting it up than a turnkey visual scenario does. The bottom line for a rollout: Make is the faster first win on a simple app-to-app automation, and Backbuild is the more governable and auditable foundation as the automations touch no-API systems and the team grows.

Strategic fit and vendor risk

An executive sponsor is evaluating fit and risk more than features: what the tool consolidates or fragments, how much it locks the organization in, and whether the vendor is a safe multi-year bet. Each product presents a different strategic shape.

Make strategic case is a mature builder, breadth, and attestations. It is an established platform with a large connector catalog, a loved visual builder, a long track record, and independent compliance attestations including SOC 2 Type II and ISO 27001, so it is a low-risk way to give teams broad, visual automation across the apps they already run, and its ownership by Celonis places it inside a larger process-automation company. The risks an executive should weigh are that its credit meter can make cost harder to forecast as AI and automation volume grow, that it automates across whatever apps the team runs rather than consolidating them, and that its reach ends at an app API.

Backbuild strategic case is consolidation, real-system reach, and model choice. The automation lives inside an all-in-one workspace spanning Mail, Chat, Meetings, Calendar, Contacts, Docs, Sheets, Slides, Diagrams, and Photos, with dedicated photo, video, training video, audio, and music editors, Files, Backbuild Finances, a built-in help desk, and the Secrets vault, it operates real systems including no-API apps under governed credentials with full audit on every plan, and it runs on the AI model of your choice. That reduces the number of vendors, extends reach past the API boundary, and puts the automation next to the data it acts on. The risk an executive should weigh in the other direction is that Backbuild is newer and pre-launch in parts, and does not ship Make visual builder or connector catalog, trading that breadth and those attestations for real-system reach, governed credentials, model choice, and workspace consolidation. The bottom line: choose Make for a mature visual builder and the broadest pre-built automation across mainstream apps from an established, attested vendor, and Backbuild for a consolidated workspace whose AI worker operates real systems under organization governance with the model you choose.

Frequently asked questions