Beyond the five core AI team members, configure bespoke designer agents for any domain-specific job your organisation needs done. No code. No deployment. Just configuration.
Generic AI platforms give you one-size-fits-all
EnGenAI bespoke agents are configured for you
Configuring an agent means setting nine parameters. All nine are set through the platform API — Keith handles this on your behalf when you describe what you need.
A natural-language prompt that defines who the agent is, what domain it operates in, and what topics it must cover. The LLM uses this to guide every conversation — no hard-coded question flows needed.
"You are a Legal Contract Reviewer. Your role is to identify non-standard clauses, flag risk areas, and summarise obligations. Do not advise on jurisdiction-specific law."
Choose which AI model powers the agent and from which provider. Use a frontier model for complex reasoning tasks, an efficient model for simple extraction. Cost and quality, tuned per agent.
claude-opus-4-6 for contract analysis · claude-haiku-4-5 for data extraction
Three-layer behavioral constraints: platform floor (inviolable), org floor (admin-set), and agent config. Lower layers can only add restrictions — never remove them. Guarantees agents cannot exceed their mandate.
"no_implementation_suggestions": true · "require_human_approval_on_write": true
Bind vetted platform capabilities to the agent. MCP-registered servers (registered via the MCP Server Registry) appear here alongside built-in platform capabilities. Each tool has a permission tier (READ / WRITE / EXECUTE / DESTRUCTIVE) and a minimum autonomy level. Agents can only use what they have been explicitly given.
web_search (READ) · write_database (WRITE, min autonomy 1) · deploy_staging (EXECUTE)
Five levels from fully human-controlled (0) to fully autonomous (4). Level 4 is reserved for internal EnGenAI agents only — customers can configure agents up to level 3. Plan tier gates maximum autonomy.
Level 1: AI suggests, human confirms each action · Level 2: AI acts, human reviews results
Connect the agent to your organisation's external systems — BI tools, project trackers, databases, any REST API — through a unified 4-layer permission model. Credentials live in GCP Secret Manager, never in the database.
Tableau (visualisation) · Jira (project tracking) · Snowflake (data warehouse) · Any REST API
An org-scoped vector store (Milvus) that grows with every session. The agent retrieves relevant prior interactions before responding — knowledge compounds. Data is strictly partitioned: one organisation's knowledge never leaks to another.
"Previously, this stakeholder mentioned the refresh cycle must be daily — reflecting that context now."
How users interact with the agent. Start with a web chat interface with topic-progress tracking. Extend to API invocation for programmatic use, or email mailbox for async stakeholder engagement.
Chat (web) · API (programmatic) · Email mailbox (async) — coming later
What happens when the agent completes its task. Route the output to a human reviewer by role (BA, architect, legal), set an SLA, and define what happens on approval or rejection. Powered by the Human Agent Integration system — see the dedicated deep dive.
On completion → assign to BA for review (SLA 24h) → on approve: export document → on reject: restart
The CTO describes what they need. Keith — the CPO agent — makes all the API calls to provision the agent. No code change. No deployment needed.
You describe the agent to Keith
"I need an agent that gathers Tableau dashboard requirements from our data stakeholders"
Keith creates the Agent Template
POST /agent-templates — sets identity, LLM, autonomy, interface type
Keith binds the tools
POST /tool-bindings — web_search, write_database, and session management tools
Keith configures steering
Behavioural constraints: no implementation suggestions, GDPR-compliant, require approval on write
Keith connects external systems
POST /connector-bindings — Tableau workspace (read-only), HTTP endpoints for your data sources
Your agent is live
Immediately available in your workspace. Gets smarter with every session.
Any agent that needs domain expertise, organisation-specific constraints, and connections to your systems. These are just starting points.
Captures stakeholder requirements for any software or data project. Guides a structured conversation, generates EARS-formatted requirements documents, and routes for human BA sign-off.
Reads contracts, flags non-standard clauses, scores risk exposure, and produces a redline summary. Escalates to legal counsel for final sign-off before any contract is executed.
Connects to your Tableau workspace, understands existing dashboard structures, and gathers requirements for new visualisations. Proposes metric hierarchies based on your data model.
Reviews code changes and infrastructure configurations against your organisation's compliance policies. Flags violations, generates audit reports, and tracks remediation.
Don't start from scratch. EnGenAI ships four pre-built Business Process Templates — fully configured agents ready to deploy into your organisation. All four have XML-structured steering enabled, delivering 15–30% fewer prompt tokens compared to Markdown format.
Extracts structured data from unstructured documents — invoices, contracts, forms. Routes extracted data for human validation before downstream processing.
Guides structured requirements conversations with stakeholders. Generates EARS-formatted requirements documents and routes to a BA for sign-off.
Connects to your data warehouse, interprets trends, and proposes predictive models. Presents findings with human-readable rationale before any model is deployed.
Receives, clarifies, and routes development requests. Decomposes work into actionable tickets, assigns estimates, and routes to the engineering team for prioritisation.
Platform templates are org-neutral — they appear in the template catalog for every organisation. Instantiate one via the API and it inherits your org's Steering Floor policies automatically. All four ship with XML-structured steering enabled.
Every session adds to the agent's knowledge store — an org-scoped vector database that is strictly private to your organisation. The more your team uses a custom agent, the better it becomes at understanding your organisation's specific context, terminology, and patterns.
Knowledge is strictly org-scoped. One organisation's data never influences another's agents.
Agent templates, tool catalog, autonomy levels, steering resolver, and human agent system — all deployed and serving requests.
Visual Agent Builder Wizard, tool catalog browser, and human task queue UI — shipping soon.
Every custom agent exposes an A2A-compatible Agent Card endpoint for standardised inter-agent discovery.
Autonomy levels above Level 2 require Pro or Enterprise plans. Starter customers build agents with human approval at every step.
See also: Human Agent Integration and Billing
Custom agents are powerful. See how every token they use is metered, billed, and visible — with pre-paid credits, auto top-up, and hard-stop protection.