Side by side
Facts about Relevance AI were read on its own pages on 2026-09-27; each cell links its source. Facts about tacitrun describe what the product enforces.
| Dimension | tacitrun | Relevance AI |
|---|---|---|
| How an agent is built | Describe the process in plain English or hand over the SOP; tacitrun compiles a process graph and composes one domain agent per step, carrying your rules and exceptions. | A "no-code agent builder" with pre-built specialist agents (Research & Enricher, Post-call Actioner and others), "built and customized by your team" with deployment teams available. [1] |
| Approval before an action | Every write to a connected system stops at the actual call — a person accepts, modifies or rejects in the Queue; the corrected version is what executes. Not an instruction the agent might skip. | "Human-in-the-loop approvals" listed as an access-control feature; the page does not describe a gate on the write itself. [1] |
| Testing before go-live | Evaluation cases derived from the process graph; an agent cannot be submitted until it passes. Then shadow mode on real work, with the agreement rate measured. | An evals system: "Set up benchmarks", pass-rate tracking, "Score live runs, not just test sets", sampling a share of live runs for quality. [1] |
| IT governance | IT approval is the go-live gate: IT connects the credentials, binds the fields and approves a locked version. Business builds, IT governs. | Role-based access control, SSO/SAML, audit logs, version control and real-time monitoring with tracing are listed. [1] |
| Systems it reaches | 42 built-in connectors plus your own REST APIs (OpenAPI) and MCP servers; all through the same approval gate. | "1,000+" app connections including Salesforce, HubSpot, Slack, Gmail, Snowflake and Zendesk. [1] |
| Your cloud, your models | Enterprise: agents run in your own GCP project on your own models (Claude on Vertex AI via Workload Identity Federation) or your own OpenAI / Azure OpenAI key. | Data residency support is listed; models are chosen and tested across providers by the platform. [1] |
| Pricing model | Flat monthly plans — Team $1,999/mo, Business $2,999/mo — with a free trial of the whole product; Enterprise custom. No per-task or per-credit metering. | Usage-based per task; the page cites an average cost per task and per-run costs that vary by agent. [1] |
| Security posture | Tenant isolation enforced in the database (row-level security), immutable audit trail, per-run traces, public DPA; SOC 2 Type II in progress — stated as such. | SOC 2 Type II, GDPR, PII masking, "no training on your data" are stated. [1] |
Choose Relevance AI when
- You want to assemble many specialist agents quickly from a template library and iterate in a builder UI.
- Usage-based pricing fits a variable, high-volume task load.
- You need a certified SOC 2 Type II report today.
Choose tacitrun when
- The process definition should come from your own SOP and stay the single source the agents, the tests and the runtime rules are derived from.
- IT approval must be a hard gate and every write must wait for a person at the call, not as an optional access-control setting.
- You want flat, predictable pricing and, on Enterprise, agents running in your own cloud on your own models.
Questions people ask
- Is tacitrun a Relevance AI alternative?
- Yes for operations teams that want governed, process-derived agents with IT approval. Relevance AI is the closer fit for a template-first, no-code agent workforce billed per task.
- Does tacitrun have evals like Relevance AI?
- Yes, with a different origin: tacitrun derives evaluation cases from the compiled process graph, so a passing agent is one that does what the process says, and it reports repeatability alongside the score. Shadow runs on real work follow before promotion.
Why offload this process to tacitrun’s AI operating layer
tacitrun is built for exactly this handoff: a business team describes the process it already runs, and the platform turns it into governed domain agents that work across the systems you have, under your IT’s approval, with every write waiting for a person.
- Built from your procedure, not a vendor template
- Describe the process in plain English or hand over the SOP. tacitrun compiles it into a process graph and composes one domain agent per step, so the agents carry your rules, your exceptions and your vocabulary.
- Tested against the process before it can act
- Evaluation cases are derived from the graph itself, so a passing agent is one that does what your process says. Then it runs in shadow beside your team on real work before anyone lets it act.
- Every write stops for a person
- The approval gate sits on the actual call to Salesforce, Shopify, SendGrid, SAP or any connected system. A person accepts, modifies or rejects; the corrected version is what executes; the trace keeps the record.
- Runs across the systems you already have
- Built-in connectors, your own REST APIs or MCP servers, and on the Enterprise plan your own cloud project and your own models. The systems of record stay where they are; the layer does the work between them.
- IT approves, business leads
- Business users build and prove; IT connects the credentials, binds the fields and approves before anything goes live. Neither side inherits the other’s risk.
Sources
Product names belong to their owners. Read on 2026-09-27; tell us if something has changed and we will correct it.
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