CrewTAC ai

COMMON PLATFORM

One AI platform. Multiple specialized agents.

The six products share common services so client integrations can be added without rebuilding the agent core.

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  • Sales Qualification
  • Customer Support
  • Document Processing
  • Operations Workflow
  • CRM Intelligence
  • Legacy Modernization

Reference architecture

How a request travels through the stack.

A call enters at the versioned API edge, is authenticated and scoped to a tenant, reaches the orchestrator, acts through the tool layer and lands in the data and observability layer as an auditable record.

  1. Client UI / External System

    layer 1

    Your product, portal, workflow tool or backend service

  2. API Gateway / BFF

    layer 2

    Versioned /v1 surface for every agent

  3. Authentication + Tenant Context + Validation

    layer 3

    OAuth 2.0 or scoped API keys, server-derived tenant_id, schema validation

  4. Agent Orchestrator

    layer 4

    Where the agent decides what to do next

    • Model Provider Adapter
    • Prompt / Instruction Registry
    • Retrieval / Knowledge Service
    • Workflow / State Machine
    • Policy & Guardrail Engine

  5. Tool & Integration Layer

    layer 5

    Vendor-specific connectors, isolated from agent logic

    • Tool Registry — schema + allowlist
    • CRM
    • Ticketing
    • Email / Calendar
    • Documents / Storage
    • Generic REST APIs
    • Webhooks

  6. Data Layer + Observability

    layer 6

    PostgreSQL · Vector Store · Object Storage · Queue

    • Logs
    • Metrics
    • Traces
    • Audit
    • Evaluation
    • Cost Telemetry

Platform features

What every agent inherits.

These are core services, not per-project add-ons. An agent gets them by being on the platform.

Multi-agent orchestration

One orchestrator runs every agent, each with its own instructions, tools and state model.

Model-provider abstraction

Providers sit behind an adapter, so a model change is configuration rather than a rewrite.

Prompt / version management

Instructions are registered and versioned, so behaviour changes are reviewable and revertible.

RAG / knowledge retrieval

Tenant-scoped retrieval grounds answers in approved sources and returns references with them.

Workflow state management

Long-running work is durable. A step that already reached an external system is never run twice, so retrying after an outage is safe.

Tool registry and permissions

Every tool declares its input schema, its impact and the scope it needs. A tool outside the workflow's allowlist is refused even though it exists.

Human approval gates

Configurable gates hold any side-effecting step until a person approves it.

Tenant isolation and RBAC

Data, configuration and credentials are separated per tenant with role-based access.

Audit logging

Inputs, decisions, tool calls and outcomes are recorded with correlation IDs.

Webhook / event support

Signed, versioned, retry-safe events keep external systems in step with agent activity.

API-first integration

Anything the UI can do is available over the API, because the UI uses the same contract.

Evaluation / regression testing

Golden cases run against prompt and model changes before they reach a client environment.

Configurable data retention

Retention windows are set per tenant and per data class rather than assumed.

Indian languages and voice

Agents detect and answer in Indian languages, including Hindi-English mixing, and can listen and speak — powered by Sarvam AI's speech and translation models.

WhatsApp and phone channels

The same agent answers on your website, on WhatsApp and on an Exotel or Twilio phone line, with one set of knowledge, caps and audit.

Spend caps and live cost metering

Set a monthly ceiling in the portal; every model, speech and translation call is metered per tenant, per agent, per day.

Private deployment

Run in your own Azure region with the database, secrets and documents on private endpoints inside your network.

Data-principal rights (DPDP)

Export or erase everything held about one person across every agent and channel, with a privacy-safe audit record.

Schedules and SDKs

Run any agent on a timetable with results posted to your webhook; integrate with Python and TypeScript SDKs.

Client integration readiness

Designed so your systems can be added later without a rebuild.

The reusable core stays clean; anything vendor- or client-specific lives at the edges where it can change independently.

  • Vendor-specific connectors remain isolated from agent logic.
  • External IDs are stored with internal IDs.
  • Side-effecting actions support idempotency.
  • OAuth / API keys can be supported through adapters.
  • Mock connectors allow demos without client credentials.
  • Client-specific configuration lives outside the reusable core.

Integration process

The nine steps from discovery to monitoring, and what we need from you.

Documentation

Quick start, API conventions, a worked example and evaluation criteria.

AI Agents

The six products that run on this platform.

Next step

Put the platform behind your workflow.

Bring a workflow and the systems it touches. We'll map it onto the platform and show you where the approval gates belong.

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