AI Solutions that ship to production - not slide decks.
We design, build, and operate custom AI agents, generative-AI workflows, and AI-powered CRM systems that move real revenue. From first conversation to live system in 4-8 weeks, with a 30-day results guarantee.
TL;DR - In one paragraph
AI solutions are production systems - not chatbot demos - that combine large language models, retrieval over your business data, and tool-use to do specific business work like sales qualification, customer support, or operations automation. Done right, they move a measurable outcome (cost-per-ticket, leads-per-rep) and ship in 4-8 weeks.
An AI solution is a production system, not a chatbot demo.
AI solutions are software systems that combine large language models, retrieval over your business data, structured tool-use, and human-in-the-loop controls to perform specific business work - sales qualification, customer support, operations automation, knowledge retrieval, or content production. Unlike off-the-shelf AI tools, an AI solution is engineered for a single job, integrated with the CRM and systems your team already uses, and monitored against measurable outcomes.
Done well, an AI solution moves a number that the business already cares about: cost-per-ticket, leads-per-rep, response time, conversion rate, headcount avoided. Done badly, it becomes another expensive demo nobody uses. The difference is in the engineering, not the model.
The AI solutions we build, end-to-end.
How an AI solution actually gets built.
Four phases, weekly demos, fixed price. No black boxes, no surprise invoices.
- 01
Discovery & scope (week 1)
Free 30-minute call, then a paid 1-week discovery sprint. We map the workflow, identify the highest-leverage automation, and benchmark candidate models on your data. You leave with a fixed-price proposal and architecture diagram.
- 02
Build (weeks 2-6)
Weekly demo every Friday. We build the agent or workflow against an evaluation suite that scores accuracy, latency, and cost. You see the numbers move every week.
- 03
Pilot (weeks 6-8)
Limited rollout to 1 team or a slice of traffic. Human-in-the-loop on. We tune prompts, add tools, fix edge cases. No production traffic until we hit the success metric.
- 04
Operate (ongoing)
Full rollout, SLA-backed monitoring, monthly iteration cycles, and a named operator. We measure leading indicators (eval scores, drift, cost) so problems are caught before users notice.
AI solutions we have shipped.
AI Agent
HeyAva - Voice-First AI Chief of Staff
Voice-first AI assistant for executives that takes meetings, drafts follow-ups, and runs daily ops.
AI-Augmented Platform
Command - Team ops platform we built and use
AI-powered task triage, EOD summaries, and KPI rollups inside a custom team operations platform.
AI-Powered CRM
Johnston Ventures - 20+ funnels across 3 brands
AI lead scoring + automated follow-up across a 20-funnel ecosystem driving consistent pipeline.
Practical questions about AI solutions.
An AI solution is a production system that solves a specific business problem - for example, a customer-support agent that handles tier-1 tickets, a sales assistant that qualifies leads, or a workflow that drafts and sends proposals. Generic AI tools (ChatGPT, Copilot) help individuals; an AI solution is engineered, integrated with your CRM and data, monitored, and owned by the business.
Most engagements ship a usable v1 in 4-8 weeks. A focused single-agent build (e.g., an SDR-style outreach agent) is typically 4 weeks. Multi-agent systems with custom tooling and integrations run 6-10 weeks. We work in weekly demo cycles so you see progress every Friday.
No - that is our job. We benchmark on your actual workload (latency, cost, accuracy on your data) before locking in a model. Most production builds end up multi-model: Claude or GPT-4 class for reasoning, smaller models for routine extraction, and embedding models for retrieval. We also abstract the model layer so you can swap providers later without rebuilding.
Three controls. First, retrieval-augmented generation (RAG) so the agent answers from your documents and data, not its training set. Second, structured outputs and tool-use schemas that constrain what the agent can return. Third, evaluation suites that we run on every prompt change so we catch regressions before users do. For sensitive flows (finance, healthcare, legal) we add human-in-the-loop approvals.
Build cost ranges from USD 6,000 to USD 35,000 depending on scope. Ongoing operations (model API costs + monitoring + iteration) typically run USD 800-USD 5,000/month. We share a fixed-price quote after a free 30-minute discovery call - no commit until you see the number and the milestones.
Yes. We use enterprise / API tiers from OpenAI and Anthropic, which contractually do not train on your data. For highly sensitive workloads we deploy on Azure OpenAI or AWS Bedrock (data stays in your tenant), or run open-weight models (Llama, Mistral) on your own infrastructure.
Most internal builds stall on the operations side: nobody owns evaluation, monitoring, error handling, or the iteration loop after launch. We bring a productized delivery process - weekly evals, prompt versioning, a monitoring dashboard, and a named operator on our team. Roughly 70% of our work is outside the prompt itself.
Book a free 30-minute AI discovery call.
We will map your highest-leverage AI opportunity, benchmark candidate models on your data, and send you a fixed-price proposal within 5 business days. No sales pitch.