The AI automation agency that runs on what it ships.

An AI automation agency designs, builds, and runs AI-powered systems for specific business work - sales follow-up, customer service, document processing, voice calls, lead qualification - and operates those systems on an ongoing retainer. Different from an AI consulting firm (advice only, no production code) and different from a no-code "Zapier shop" (automation without the AI layer or the evaluation discipline). The category exists because most SMBs want the outcome (an AI receptionist that books appointments, an AI follow-up agent that recovers cold leads) without hiring a full AI engineering team.

Three differences worth checking against the market. (1) We run on what we sell. Our internal ops platform, our voice AI assistant (AVA), our outbound systems - all built on the same stack we ship to clients. If it works for us, it ships. If it does not, we know before you do. (2) Fixed-price builds with a 30-day results guarantee. Most agencies bill hourly, which punishes speed and rewards drag. We scope, fix-price, and back results in writing. (3) Operating model, not project model. After we build, we stay on retainer to run the system, measure outcomes, and iterate weekly. About 70 percent of our revenue is recurring operate-and-improve work, not one-off builds.

Discovery, build, operate, iterate. Discovery: map your workflow, identify which work an AI agent can take over, benchmark models (Claude, GPT, Gemini, open-weight) against your real data, scope a build with hard numbers. Build: ship the AI agent or workflow with monitoring, evaluation, and a tested CTA path. Operate: monitor weekly, tune prompts, swap models when a better one ships, integrate new data sources. Iterate: every 30 days we review the agreed business metric (cost per ticket, leads per rep, response time) and either celebrate the win or fix what is not working.

Realistic numbers. Discovery sprint: USD 1,500 for 1 week (workflow map, model benchmarks, fixed-price build proposal). Focused pilot: USD 6,000 to USD 12,000 for one agent or one workflow, 4-6 weeks. Full automation program: USD 25,000 to USD 75,000 build plus USD 2,500 to USD 7,500 per month operate-and-iterate retainer. Voice AI deployments start at USD 4,000 build plus USD 497 per month. Compare this to: in-house AI hire (USD 150K-USD 250K per year fully loaded), a generic SaaS subscription with no customization (cheaper but rarely solves the specific workflow), or a Big Four consulting engagement (10x our pricing for slide decks).

In-house team makes sense if you have a sustained roadmap of AI work that justifies a full-time AI engineer (USD 150K-USD 250K per year, 4-8 weeks to hire, ongoing management). SaaS subscription makes sense for commodity workflows where a packaged product like ChatGPT Enterprise, Intercom Fin, or Reply.io already does 80 percent of what you need. Agency makes sense when (a) you have a specific business outcome you want shipped (not a tools budget to spend), (b) the workflow has enough custom logic that off-the-shelf SaaS misses it, and (c) you want someone accountable to a measurable outcome, not to a billable hour count. Most SMBs we work with land on agency for the first 12-18 months, then either stay on retainer or transition specific systems to in-house once volume justifies it.

Yes. About 60 percent of current engagements are USA, UK, Canada, and Australia. We work in Indian Standard Time (IST) with overlap into US Eastern morning and full UK/EU hours. Async-first delivery: weekly demos, written status, Loom walkthroughs, response within 4 business hours. We have shipped systems for clients in California, New York, Texas, Ontario, British Columbia, London, and Sydney. Live English voice agents, GHL automation, and CRM AI all work cross-border with no degradation.

Our strongest verticals are real estate, healthcare and med-spa, professional services (law, finance, consulting), e-commerce, education, agencies, and SaaS. The patterns transfer across sectors - the difference is mostly which integrations matter (DocuSign, Stripe, HubSpot, GHL, EHR) and which compliance constraints to design around (HIPAA, PCI, GDPR, India DPDP). We have shipped working AI automation in all seven verticals, with reference case studies for each.

Realistic timelines. Discovery sprint: outputs in 1 week. Focused pilot (one agent, one workflow): live in 4-6 weeks. Full multi-system program: phased over 3-4 months with weekly demos. Voice AI deployment: 7-14 days from contract to live calls. We do not ship slide decks - every milestone is a working demo. The 30-day results guarantee means if we have not moved the agreed metric within 30 days of launch, we keep working at no charge until we do.

Model layer: Claude (Anthropic) and GPT (OpenAI) as primary, Gemini and Llama for specific workloads after benchmarking. Voice: ElevenLabs and Deepgram. Automation: n8n, Make, and custom Node.js services. CRM: GoHighLevel (we are an early partner since 2017), HubSpot, Salesforce. Infrastructure: AWS, Cloudflare, Hostinger VPS for low-overhead deployments. We are model-agnostic by principle - we benchmark on your real data before locking in a vendor, not the other way around.