AI Automation Agency & Enterprise AI Consulting
BMG connects your business data into a shared context layer and deploys AI agents that automate reporting, lead routing, and operations. Enterprise AI consulting that produces working automation — not a roadmap on a slide.
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AI without business context is a sophisticated guessing machine.
Most enterprise AI projects stall for the same reason: the AI does not know your business. It does not know your customers, your pricing, your operations, or your historical data. It works from isolated prompts and produces outputs that require hours of human correction before they are usable. The result is a team that spent six months on an AI initiative and is still doing the same work manually.
Our enterprise AI consulting practice starts with the context problem. Adeqo ACE connects your CRM, ad platforms, operational systems, telephony data, and custom sources into a shared business model — a normalized representation of your customers, campaigns, leads, locations, and performance history that AI agents can reason from without hallucinating or misinterpreting. This is not a data warehouse project. It is a targeted integration that takes weeks, not years.
Pable agents are then deployed on top of this context layer to automate specific workflows: monitoring campaign performance and flagging anomalies before budgets overspend, routing leads based on intent signals and CRM history, generating weekly performance reports with narrative analysis, and triggering operational alerts when key metrics move outside expected ranges. Every agent runs on real business data and operates within the approval boundaries your governance requires.
BMG's enterprise AI consulting practice is built around Adeqo ACE (context layer) and Pable (agent platform). We scope, build, and operate automation programs — not just design them.
What our AI automation practice covers
Business Context Layer (Adeqo ACE)
We connect your CRM, ad platforms, operational systems, and custom data sources into a shared context model. AI agents reason across this unified layer — not from isolated database snapshots or disconnected API calls.
AI Agent Deployment (Pable)
Pable agents monitor approved workflows, surface anomalies, route leads, generate reports, and trigger alerts — with human approval steps where your governance requires them. Agents act on real business data, not generic prompts.
Reporting & Analytics Automation
We automate the reports your team rebuilds manually every week: campaign performance summaries, pipeline health reports, operational snapshots by location. Typically reduces manual reporting time by 6–12 hours per team per week.
Lead Routing & Qualification Automation
AI-assisted lead scoring and routing that goes beyond simple HubSpot rules. We build models that evaluate lead fit, intent signals, and historical conversion data — then route leads to the right rep or sequence automatically.
Enterprise AI Strategy & Roadmap
Before we deploy anything, we run a two-week discovery to map your data sources, existing automations, and governance requirements. The output is a prioritized roadmap of automation programs by business value and implementation complexity.
Ongoing AI Operations
AI automation requires maintenance: models drift, data sources change, and new workflows become automation candidates. We provide ongoing operations support — monitoring agent performance, retraining where needed, and expanding the program as you scale.
Common questions
- What makes BMG different from a general AI consulting firm?
- Most enterprise AI consulting firms design the strategy and hand you a roadmap. BMG builds and operates the system. Our in-house engineers implement the data connections, build the agents, and manage the ongoing operations. We are accountable to the outcomes, not just the recommendations.
- What data sources can you connect to?
- We connect to HubSpot, Salesforce, Google Ads, Meta, GA4, Shopify, custom databases, telephony systems, ERP platforms, and flat-file data sources. The context layer (Adeqo ACE) normalizes data across these sources so agents can reason across them without requiring a full data warehouse migration.
- How long does an enterprise AI consulting engagement take?
- Discovery and scoping takes two weeks. The first automation program typically goes live within 6–10 weeks. We scope only what will actually ship — not a theoretical roadmap that sits on a slide for eighteen months.
- What workflows are best candidates for AI automation?
- The best candidates are high-frequency, rule-based processes that currently require manual effort: lead qualification and routing, performance reporting, anomaly detection in ad accounts, content updates triggered by data changes, and operational alerts. We identify the highest-value automation candidates during the discovery phase.
Ready to see which workflows are automation candidates?
Book a strategy call. We will map your data sources, identify the highest-value automation opportunities, and scope a program that ships — not a plan that sits.