agents · CAT-30030941 · rev 1.0|
Relevance AI Specialist Agents. @relevance-ai-specialist-agents
5.0Reviews ▾
Rated 5.0 / 5 by clients on GoodFirms.
Read verified reviews on GoodFirms →Vetted by Scrums.com Platform
Provider Relevance AI
Last review 2026-08-14
What you get
the numbers that matterPriced on scope
billed monthly
≈ 2 weeks
signed to first PR
96%
engagements renewed
96%
to your stack & domain
Specialist AI agents and multi-agent teams from Relevance AI for autonomous work connected to enterprise tools and data.
How this operator works
every way of working, already decidedOwns the system, not the ticket
Takes end-to-end ownership of a service or surface. Design, delivery, on-call. And is measured on outcomes, not hours.
Embedded, async-first, instrumented
Works inside your repos, your CI and your rituals. Daily written standups, decisions logged. No status-meeting tax.
Runbooks, canaries, reversible deploys
Every change gated and reversible. Incidents get a timeline and a postmortem; nothing ships without a rollback.
Plugged into your Slack & rituals
Joins standups and retros, reports weekly against the goal. You get an operator, not a queue.
Brings a pre-wired stack or adopts yours
Infrastructure and observability as code by default. No bespoke setup tax to absorb.
Scoped, gated, reversible
Week-1 shadow, week-2 ownership, swap on request inside the trial window. No long-tail handover risk.
Overview
Relevance AI provides specialist AI agents and multi-agent teams for autonomous work. Each agent is built for a defined role and connected to enterprise tools and data; agents can also work together as teams, passing work between specialist roles the way a human team does.
Through Scrums.com, Relevance AI Specialist Agents is listed on the catalog and deployed by Scrums.com delivery teams. They integrate it into your stack, apply your governance rules, and track its operation on the SEOP.
What it does
Specialist agent roles
Agents are scoped to specific roles and processes rather than acting as one generic assistant.
Multi-agent teams
Multiple agents coordinate on work, so multi-step processes can be split across specialist agents.
Enterprise tool connections
Agents connect to the tools and data your teams use, grounding their work in your systems.
Autonomous task execution
Within their scope, agents carry tasks end to end, escalating when a human decision is needed.
Deploying it with Scrums.com
- Scope. Scrums.com runs a fit assessment against your workflows and governance requirements, including the roles and processes to hand to specialist agents.
- Integrate. Scrums.com engineers wire it into your repos, pipelines and tools with guardrails, configuring the agents and teams and connecting your tools and data.
- Operate. The deployment runs under governance, with usage and outcome reporting via the SEOP.
Commercial availability
Relevance AI is sold as commercial SaaS by Relevance AI. Procurement runs through Relevance AI; Scrums.com supports the commercial process as part of a deployment.
FAQs
How is this different from one general-purpose assistant?
A general assistant answers what it is asked. Specialist agents are scoped to roles with their own tools and instructions, and can be composed into teams for multi-step processes.
What does deployment need?
A Relevance AI workspace, connections to the tools and data in scope, and role definitions for each specialist agent.
How is autonomy governed?
Each agent's scope, tools and escalation rules are explicit configuration. Scrums.com sets these with you and the SEOP records what agents do in operation.
What's included
in every engagement · no add-onsTrack record
deployments on real systems · anonymizedWorks inside your stack
surfaces this operator binds toBoundaries
what to deploy insteadScoped to this discipline. For an adjacent capability, compose a second operator into the squad. compose →
Not a fractional advisory engagement. For advisory-only, contact platform@scrums.com.
Deployments
the only social proof we publish402deploys
across 38 organizations
+24 last 30 days · median age 11.4 mo · retention 96%
Live telemetry
this operator's system surfacePricing
one number · one footnotePriced on scope
All-in: the operator, delivery manager and replacement guarantee. No recruiter fee, no markup surprises.
Final pricing computed at deploy from your committed envelope, region and account tier.
FAQ
common questionsHow is Relevance AI Specialist Agents priced?+
Priced on scope. Request a quote and pricing is computed from the work envelope.
Is Relevance AI Specialist Agents available now?+
Yes. It is published and deployable directly from the Scrums.com catalog.
Can a Relevance AI Specialist Agents deployment be reversed?+
Yes. Deployments are reversible with a one-click swap inside the trial window.
Who provides Relevance AI Specialist Agents?+
Relevance AI, vetted by the Scrums.com platform.
How it compares
vs other agents| Option | From | Stack | Status |
|---|---|---|---|
| Relevance AI Specialist Agents · this one | Priced on scope | agent · ai-agents · multi-agent | ● available |
| Qdrant MCP Server | Priced on scope | mcp · qdrant · vector database | ● available |
| Pinecone MCP Server | Priced on scope | mcp · pinecone · vector database | ● available |
| Databricks SQL MCP Server | Priced on scope | mcp · databricks · sql | ● available |
Commonly deployed with
more agentsQdrant MCP Server
Qdrant MCP Server gives approved AI clients access to qdrant vector-memory workflows for storing and retrieving semantically relevant context. It is most valuable where teams want to provide engineering agents with an explicit semantic memory or retrieval layer for code and technical knowledge.
Pinecone MCP Server
Use Pinecone MCP Server to connect engineering agents with pinecone documentation, index management, upserts and vector queries. The key operational benefit is to let AI engineers build and operate retrieval systems directly from their coding agents.
Databricks SQL MCP Server
Databricks SQL MCP Server is a first-party MCP surface for aI-generated SQL against Unity Catalog tables with read/write governed by Databricks permissions. The engineering-leadership use case is straightforward: connect engineering and data agents to governed SQL execution over enterprise data.
Priced on scope