Solution

Automate the operations bottleneck.Production agents for triage, support, ERP workflows, and content.

Enterprise automation is where agentic AI pays back fastest: operational triage, customer support, ERP-integrated workflows, content-at-scale pipelines. Concrete inputs, measurable outputs, decisions you can audit. We design, build, and ship these systems end-to-end — and your team owns the code.

2–4×
throughput per operator / reviewer
< $5
average cost per agent-handled decision
6–10 wk
first agent in production
Full
audit trail per decision
Use cases

Operational automations that ship reliably

Ticket triage + L1 support

Classify, contextualise from CRM / ERP, draft response, escalate complex cases with a pre-filled handoff brief.

ERP-integrated customer workflows

Odoo / SAP / NetSuite MCP servers behind a supervisor agent that handles customer queries with full ERP context.

Content + SEO pipelines

Research → outline → draft → review pipelines for teams producing content at scale.

Document processing

Invoice / contract / KYC document extraction with structured outputs and validation.

Sales lead qualification

CRM-integrated qualification agents that score inbound leads, pull context, draft outreach.

Compliance review

Layered-guardrail document review for regulated workflows — see the AI Guardrails solution for the full pattern.

Industries served
IT ServicesERP / Enterprise SoftwareFinancial ServicesHealthcare OperationsReal EstateEdTech
Technology

Enterprise automation stack

Reasoning modelsClaude Sonnet 4.6 (default) · Haiku 4.5 (routing)Tool layerMCP servers wrapping your ERPs, CRMs, internal APIsOrchestrationSingle-agent or supervisor-pattern depending on workflowObservabilityLangfuse · per-decision cost · audit logDeploymentYour runtime — containers · queues · existing CI/CD
Methodology

Delivery process

01

Workflow audit

Pick the operational workflow with clear inputs / outputs / measurable steps. Skip creative or open-ended workflows for the first ship.

02

Architecture

Agent role(s), tool registry, integration points, observability, eval plan, audit requirements. Reviewed with your operations and engineering leads.

03

Implementation

Production-grade code on your stack. Staging environment from week 2.

04

Parallel-run

Agent runs alongside the existing manual workflow for 1–2 weeks. Outputs compared. Errors triaged.

05

Handoff

Documentation, eval-set update process, monitoring dashboards. 30/60/90-day check-ins.

Security & scalability

Security & scale for operational agents

Read-only by default

Mutating actions are added deliberately. Where they exist, they go through approval queues or human-in-the-loop gates above defined risk thresholds.

Per-decision audit log

Every agent decision logs inputs, tools called, model used, output, cost, and (where applicable) the human approver.

Cost discipline from day one

Per-workflow cost tracked. Most automations land under $5 per decision in steady state.

Graceful failure

Every agent has a fallback path. If the agent cannot handle something confidently, it escalates with full context — it does not guess.

Integrations

Systems we automate against

  • Odoo · SAP · NetSuite · Microsoft Dynamics
  • Salesforce · HubSpot · Zoho · Pipedrive
  • Zendesk · Freshdesk · Intercom · custom ticket systems
  • Slack · Microsoft Teams · WhatsApp Business · email
  • PostgreSQL · MySQL · MongoDB · custom data stores
  • Stripe · Razorpay · custom payment / billing systems
Business impact

Why operational automation is the highest-leverage start

Operational workflows are where the inputs and outputs are most concrete and the measurements are most defensible. They are also where the manual cost is most visible, which makes the business case easy.

2–4×
throughput per operator
~70%
of L1 cases handled without human touch
< $5
cost per agent-handled decision
6–10 wk
time-to-production
Case studies

How recent engagements actually shipped

ERP / Enterprise Software · 8 weeks discovery → handoff

ERP support triage agent eliminates the Level-1 backlog

Odoo-based ERP partner · Gujarat · ~60 implementation consultants

Problem

Customer support backlog had grown to ~340 open tickets. Level-1 triage took 12–20 minutes per ticket on average, and 35% of tickets were misrouted on first pass — every misroute became a customer-facing escalation churn.

Solution

A supervisor-pattern agent that ingests email and form submissions, classifies the issue, queries the customer's Odoo instance for context (open invoices, recent modules, last login, current contracts), drafts a Level-1 response with the right module screenshots inline, and routes complex tickets to the right consultant with a pre-filled handoff brief.

Claude Sonnet 4.6 (drafting)Custom MCP server: Odoo (read-only customer / order / invoice scope)Supervisor patternPydantic schemas
340 → 18
open L1 backlog within 6 weeks of go-live
~60%
L1 staffing reduction on agent-eligible categories
$2.30
average cost per agent-resolved ticket
8 wks
engagement, discovery to handoff
Read the full case study
Deep dives

Read what we publish on this

Architecture

Claude’s Fermat Last Theorem Lean formalization: what Prove2Me multi-agent orchestration means for verification workloads

On September 4, 2026 Anthropic reported that Claude agents produced the first complete computer-checked proof of Fermat’s Last Theorem in Lean after 11 largely autonomous days on Prove2Me. The result is a practical blueprint for long-horizon multi-agent verification, not only a mathematics milestone.

Read the post Production

GitHub Copilot’s September 4 wave: GPT-6 Astra GA, Agent Merge preview, and how to govern the new model lanes

On September 4, 2026 GitHub made GPT-6 Astra generally available in Copilot and published a weekly release that expands Fable 5.1 and Gemini 3.8 Flash access while putting Agent Merge into public preview. This guide covers what changed and how enterprises should enable the new agentic coding lanes.

Read the post Production

GPT-6 Astra for enterprise agents: Critical cyber designation, routing decisions, and the September 2026 rollout checklist

OpenAI released GPT-6 Astra on September 3, 2026 as its most capable broadly deployed model for coding, computer use, research, and long-horizon agent work. It is also OpenAI’s first model to reach Critical cybersecurity capability under the Preparedness Framework. This guide explains what changed, who should enable it, and how to route it safely against Sol and Fable 5.1.

Read the post Production

Muse Spark 1.3 for agentic coding: what Meta changed, how to route it, and when it belongs in your stack

Meta released Muse Spark 1.3 on September 2, 2026 with stronger long-horizon agent collaboration, cleaner coding style, and lower tool-call overhead. The model is available through Muse Code and the Meta Model API. This guide explains the practical routing implications for platform and engineering teams.

Read the post
Frequently asked

AI Automation for Enterprises — questions buyers ask

Scope your first operational agent

Bring the workflow you want to automate. We map the agent boundary, the integration points, and the expected cost / throughput in a 60-minute scoping session.

Adjacent

Topics & solutions worth reading next

Topic Pillar

Agentic AI

Designing, building, and shipping production agents.

Topic Pillar

Model Context Protocol (MCP)

The open protocol that gives agents tools.

Topic Pillar

AI Engineering

The discipline of shipping AI systems, not demos.

Topic Pillar

Enterprise AI Automation

Operational agents for IT services and enterprise teams.

Solution

Agentic AI Consulting

Designed, built, and handed off — production agentic systems for enterprise teams.

Solution

MCP Integration

Custom Model Context Protocol servers that turn your systems into agent tools.

Solution

AI Guardrails

Multi-layer safety, policy, and audit controls for agents in regulated environments.

Solution

Enterprise AI Architecture

Reference architectures for organisations standing up an AI platform — not one agent, but the foundation for many.

Solution

Multi-Agent Workflows

Supervisor + handoff orchestration for portfolios of agents that need to cooperate without arguing.