DRS Automation Group publishes what it ships. Capabilities validated in production. Active research threads we're studying. The technical stack we're qualified to operate against. And field notes — short observations from real engagements, written for operators considering artificial intelligence.
Every capability listed here has been deployed, tested, and operated for real clients. No pilots. No proofs-of-concept. Production systems with real customers on the other end of the line.
Full conversational AI handling inbound calls — greeting, qualification, scheduling, dispatch routing, escalation. Live in production with sub-second latency.
Lead-qualification and multi-day follow-up agents over native SMS. Handles inbound, drips outbound, books appointments directly into client calendars. Sub-30-second response time on first reply.
Real-time skill-matrix routing with day-off detection, geographic radius enforcement, and load balancing. Pulls live spot-truth from the field-service system; never books a tech who isn't working.
Brand-voiced conversational AI on Instagram DM, Facebook Messenger, and WhatsApp. Handles inbound qualification, routes to booking, escalates hot prospects. Three brands in production.
Bidirectional integrations with major field-service platforms — FieldRoutes, HubSpot, Zoho, custom CRMs. Real-time spot reads, write-back of confirmed appointments, lead capture into the right pipeline stage.
Heartbeat monitoring, OpenRouter credit alerts, FieldRoutes rate-limit tracking, daily metrics aggregation, automated daily snapshots. Watchdog runs every 15 minutes.
A handful of research threads we're actively investigating. Each one ties to a specific operator problem we believe artificial intelligence will reshape in the next 18-36 months.
We're documenting performance differentials between vertical-AI systems (engineered for one industry) versus horizontal-AI receptionists deployed at the same operator. Early data suggests vertical agents close 30-50% more qualified bookings per hundred calls handled. Working paper in progress.
Benchmarking Claude, GPT, and open-source models across the specific tasks operators care about — lead qualification, scheduling logic, dispatch decisions. Optimizing for the precision-per-dollar curve at production volume, not for benchmark scores.
Built and deployed a Phase-B optimization layer that auto-assigns the optimal technician on every booking — skill matrix, day-off detection, real spot occupancy load balancing. Eliminated dispatch overhead for the first PestPilot deployment.
Building a public taxonomy of failure modes we've observed in production voice deployments — silent failures, schema-drift errors, latency cliffs, escalation logic gaps. The goal is a shared vocabulary the industry currently lacks.
Mapping the characteristics that determine when a custom build is productizable into a vertical operating system versus when it should stay bespoke. Pattern recognition across pest control, automotive, mentorship, and field services.
DRS isn't a certifications-on-the-wall firm. We're qualified by the systems we've shipped and continue to operate. Every technology listed here is in active production for at least one client.
The bias is intentional: we go deep on the platforms that matter to operator-led businesses, instead of broad on every framework. When we recommend a stack, it's because we've run it under load.
If your business runs on something we haven't operated against, we'll tell you — and either bring in a vetted specialist or refer you to someone better suited. Honesty about scope is part of the qualification.
Working observations from real engagements. Written for operators considering artificial intelligence — and for ourselves, so the firm's institutional knowledge compounds.
Across every operator-led business we've worked with — pest control, auto dealerships, field services — speed of first response correlates more strongly with closed business than any other lever. Sub-30 seconds beats every other variable, including pitch quality.
SHORT · 2 MIN READThe thing operators call "the AI didn't work" is rarely the AI — it's the connection between the AI and the system of record. CRM write-backs failing silently. Calendar slots that don't exist getting offered. The model is fine; the plumbing isn't.
SHORT · 3 MIN READA generic AI agent gets good at the first 80% of pest-control conversations quickly and then stays there. A vertical agent built for pest control keeps improving — because every edge case the firm encounters becomes part of the system. The narrower the scope, the steeper the learning curve.
SHORT · 4 MIN READWe ship every system into production before sending the final invoice. It looks risky on paper. In practice it accelerates client decision-making and weeds out the operators who wouldn't have signed off anyway. The system has to actually work for the relationship to actually start.
SHORT · 3 MIN READBook a 30-minute discovery call or request an in-depth evaluation. We'll bring the thinking, the stack, and the production track record to bear on your specific business.