When the productized layer isn't enough — when you need real internal apps, custom workflow agents, knowledge systems on your own data, or predictive ML — this is where we leave templates behind. 24 services across 5 categories, all delivered with the same engineering rigor that makes AI ship reliably in production.
Productized stacks ship fast because they don't try to know your business deeply. They handle the calls, the bookings, the reminders — the stuff every SMB has in common. Custom engineering starts where your operation diverges from everyone else's: the spreadsheet that runs your business, the legacy software with no API, the knowledge that lives in one person's head, the data your existing tools can't connect.
Multi-tenant Postgres, role-based access, audit logging, eval pipelines, observability, cost monitoring. The unsexy parts that make production AI different from a Jupyter notebook on someone's laptop.
No vendor lock-in baked into your AI Workflows. Provider routing, fallback paths, cost-tracking middleware. Pricing and capability shift fast — your system shouldn't break when they do.
Discovery, scoping, build, launch, maintenance — same engineer through the engagement. Not a sales rep handing off to a delivery team handing off to a support queue.
Custom Tier doesn't start with a fixed quote on day one — your operation is too specific for that to be honest. We start with a paid scoping engagement that produces a real architecture, real milestones, and a fixed quote you can compare against alternatives.
Free 30–60 minute call. We map what you're trying to do to the service catalog, identify whether one service or a bundle is the right answer, and determine whether the project is fundable. If we don't think we can deliver enough value to justify the engagement, we'll tell you on the call.
Fixed-fee scoping engagement. 3–6 stakeholder interviews, system audit, technical architecture sketch, milestone breakdown, fixed-quote SOW. Output is yours regardless of whether you proceed. If you proceed within 60 days, the scoping fee credits 100% against the build.
Weekly written status updates. Bi-weekly demo calls. Mid-build milestone review with go/no-go. Pre-launch testing window with your team. Manual smoke test against a written test plan. Standard quality gates on every engagement, regardless of size.
Every build closes into a maintenance retainer covering hosting, monitoring, bug fixes, minor enhancements, and an LLM API baseline. Quarterly business reviews surface follow-on builds when the business changes. Year-2 LTV from a single Custom client often exceeds $50k cumulative — but the retainer is month-to-month, not locked in.
Each service is a distinct engineering engagement with its own target customer, technical scope, and engagement format. Most clients buy one service initially and add a second or third as the relationship deepens.
Replace spreadsheets and patchwork tools with real internal applications. The unifying pain: the owner-operator is doing daily mental arithmetic across five tools that should be one. Highest-volume custom engagements.
Single dashboard pulling from all your SaaS tools. Daily revenue, traffic, anomalies, action items, and an AI-generated daily summary in plain English. Mobile-responsive, role-aware, multi-user.
See full details →Real Postgres-backed multi-user web app replacing 3+ spreadsheets. Forms, lists, search, filters, exports, scheduled jobs. Day-1 sheet migration. Optional AI assist on data entry.
Discuss this build →Voice memo or rough notes in, branded PDF/DOCX out. AI extracts scope, pricing engine applies your rate book, payment link embedded. Tracks quote status and triggers follow-ups.
See full details →Categorizes inbox by urgency and topic. Drafts replies in your voice (fine-tuned on your sent folder). Handles routine categories autonomously where authorized. Always human-in-loop on send for non-routine.
Discuss this build →Resume ingestion, AI scoring against role requirements, auto-screening interview questions, calendar-integrated scheduling, structured interview scoring, hiring decision dashboard. Decision support, not decision automation.
Discuss this build →End-to-end agent and workflow systems that handle multi-step processes spanning multiple tools. Higher-effort, higher-margin. Computer-use agents in particular are a competitive position productized stacks can't touch.
Stateful workflow orchestrator. Form submission triggers multi-step process: extract data, draft contract, send for signature, create folders, set up project, schedule kickoff, send invoice. Failures route to human queue with full context.
Discuss this build →Anthropic computer-use agent drives the GUI like a human. Configurable tasks, screenshot logging for audit, error recovery, human takeover when stuck. The highest-moat service in the catalog.
See full details →Onboarding sequence orchestrator. Walks customers/employees through stages with personalized messaging, schedules kickoff, ensures provisioning happens, nudges when stuck, escalates to human when needed.
Discuss this build →Approval workflow primitive. Define approvers, sequence, deadlines, escalation. Automated reminders, dashboard view of pending, audit log, e-signature integration, AI summary for approvers.
Discuss this build →The "your business as software" category — capturing, structuring, and operationalizing knowledge and documents that currently live in heads, drives, and PDF folders. Strong template economics across vertical engagements.
Real RAG system — not a toy chatbot. Hybrid retrieval, citation generation, eval suite, continuous improvement loop. Slack/Teams/web interface. Permission scoping. The technical moat against productized competitors.
See full details →Single intake drives generation of full document packet. Templates with merge fields, conditionals, optional sections. AI fills structured fields and writes bespoke sections in your voice. DocuSign integration.
See full details →Owner records themselves doing a task once. Agent watches, transcribes, analyzes screen content, structures into a step-by-step SOP with screenshots, decision points, exception handling. Searchable library.
Discuss this build →Generate consistent training modules with quizzes from existing material. Track completion, assign by role/location. Periodic refreshers triggered automatically. Manager dashboard.
Discuss this build →Continuous monitoring agent. Ingests records, maps to applicable regs, maintains current compliance state and gaps list. Generates audit packets on demand. Pre-audit dry-run reports. Alerts on expiring certifications.
Discuss this build →Data engineering with AI on top. These engagements pay for themselves in the first cycle and create irrefutable proof points ("we found you $30k of margin"). Strong referral generators.
ML model trained on historical data — attributes, usage, engagement. Identifies high-risk customers 30–60 days before churn. Triggers personalized reactivation. Dashboard with at-risk list and intervention status.
Discuss this build →12–24 months of transactions analyzed. Item-level margin, demand elasticity proxies, frequency. Recommends specific price changes with projected revenue/margin impact. Pays for itself in the first cycle.
Discuss this build →Per-SKU forecast model from POS sell-through history. Reorder recommendations with quantity and timing. Auto-generate POs for review. Track aging inventory and recommend markdowns.
Discuss this build →POS revenue + Google Ads + Meta + TikTok + email + Yelp + GBP unified. Best-effort multi-touch attribution. Weekly automated report with insights. Plain-English Q&A on the data.
Discuss this build →Reviews, tickets, social mentions, surveys clustered by theme. Surfaces emerging issues before they trend. Monthly report: top 5 things customers love, top 5 issues, recommendations per issue.
Discuss this build →Read-only integration with bookkeeping platform. Suggested categorizations, anomaly detection, cash flow forecasting. Pre-close check daily. Augments — never replaces — your accountant or bookkeeper.
Discuss this build →Revenue-team intelligence layer. Attaches directly to revenue, which makes ROI conversations easy. Highly bundleable — these services pair naturally with one another.
Before each scheduled meeting, agent researches the prospect: company, recent news, LinkedIn signals, shared connections, prior touch history. 1-page brief in the rep's hands the morning of the call.
Discuss this build →Internal AI assistant connected to POS, CRM, accounting, project tools. Tool-augmented — generates real queries, never hallucinates numbers. Memory of prior conversations. Read-only guardrails.
See full details →Capture meetings (with consent), extract structured action items with owners and dates, automatically update CRM, draft follow-up emails for review, monitor follow-through. Pairs strongly with #21.
Discuss this build →Per-account health score from usage signals, invoice history, sentiment, project status. Alerts on declining accounts and expansion opportunities. Account-manager dashboard with action recommendations.
Discuss this build →Custom engagements compound when we work the same vertical multiple times — connector libraries mature, prompts get tuned, edge cases get caught up front. Our priority verticals reflect where we already have depth.
Med spas, salons, fitness studios, dental groups, auto. Operations cockpits, churn prediction, document automation, and HIPAA-conformant builds for regulated practices.
Explore →HVAC, plumbing, electrical, remodelers, pool/spa. Quote generators, dispatch tools, customer-facing portals, and computer-use agents for the legacy software your trade still runs on.
Explore →Law, accounting, financial advisory, agencies, consultancies. Document automation, knowledge agents, meeting intelligence, custom assistants on firm data.
Discuss →A 30–60 minute discovery call confirms which service or bundle fits, whether the project is fundable, and what the next step looks like. Most engagements that proceed do so via a paid scoping engagement that produces a real architecture and a fixed quote.