AI systems built for how your business actually works.
We build custom AI for businesses that have outgrown off-the-shelf tools. Chatbots, voice agents, automation, data pipelines, dashboards. Whatever fixes the thing eating up your team's time.
Custom-built, not off-the-shelf.
Most AI tools are made to fit every business, so they rarely fit yours. Maybe your workflow has quirks the tool can't handle, your data lives somewhere it can't reach, or the output isn't what you need. So we build one system for one problem, and you own it.
Where AI systems create operational leverage.
If your team spends hours each week on the same repetitive task, there's probably an AI tool worth building. Here are some common ones. If yours isn't listed, it likely still fits. Tap any to expand.
Turn hundreds of sources a week into one short briefing your team actually reads. Different agents cover different topics, then one writes it all up. It does the reading so your people don't have to.
Reads long, dense documents like contracts, filings, and specs, and pulls out what matters. It summarizes them, flags anything odd, and hands back clean notes your other tools can use.
Chat and phone agents that talk to your customers in plain language. They answer questions, qualify leads, book appointments, and take messages, then hand off to a real person when it matters.
Watches your sources around the clock, news, prices, competitors, whatever you care about, and only flags what you need to act on. Less noise, nothing missed.
Pulls clean data out of messy sources like PDFs, scans, and emails. You get organized records that drop straight into your other tools.
Dashboards that pull your data into one place, in the format your team actually uses. Real-time, and built around the decisions you make.
Hand off a repetitive, multi-step task and let an AI agent run it from start to finish across your tools. If you can say "every time X happens, we do Y," it can probably be automated.
Fast, modern websites and web apps, built to the same standard as the AI work. From a clean marketing site to internal tools and client portals. This site is one of them.
We don't sell you a product. We build it for you.
Why custom builds outperform off-the-shelf AI.
Off-the-shelf tools
- General-purpose; fits the average use case
- Output format dictated by the vendor
- Limited integration with your tools
- Pricing scales with seats / usage
- You don't own the IP
Custom-built systems
- Built for your specific workflow
- Output in the format your team needs
- Integrates with your data and dispatch
- Fixed build cost + optional maintenance
- You own the codebase
Got a task that eats your team's hours?
Start with a free 15-minute call. We'll map out what we'd build and roughly what it would take.
Book a discovery call →If your team spends measurable hours each week on a repetitive task, whether that's answering customers, reading documents, chasing data, monitoring sources, or running a manual process, there is usually a system worth building. The patterns below are common, not exhaustive. Tap any capability for detail.
Synthesize hundreds of sources per week into a focused briefing your team actually reads.
- Inputs: news feeds, newsletters, internal docs, APIs
- Output: a recurring briefing in your format and cadence
- Built in: source-grounded verification before dispatch
First-pass extraction, classification, and summarization of dense source material.
- Inputs: contracts, filings, policies, specs
- Output: structured summaries, extracted clauses, flagged anomalies
- Built in: a human-review queue for anything low-confidence
Chat and phone agents that handle real conversations with your customers: answering questions, qualifying leads, booking appointments, and taking intake.
- Inputs: your scripts, knowledge, and escalation rules
- Output: answered questions, qualified leads, captured intake
- Built in: a clean handoff to a person when it matters
Watch sources continuously and surface only what your team needs to act on.
- Inputs: the sources and signals that matter to you
- Output: targeted alerts, scored and de-duplicated
- Built in: tunable thresholds so noise drops over time
Pull structured data from messy, unstructured sources.
- Inputs: PDFs, scans, emails, web pages, exports
- Output: clean structured records in your schema
- Built in: validation and confidence scoring per field
Internal tools that aggregate signals in the format your team actually uses.
- Inputs: your data sources, plus AI-derived signals
- Output: an internal tool your team opens every day
- Built in: the views and aggregations your decisions need
Hand an entire repetitive, multi-step workflow to a custom AI agent that runs it end to end across your tools.
- Inputs: the task you keep doing by hand, and the tools it touches
- Output: the work done end to end, with exceptions flagged for review
- Built in: guardrails and a human in the loop where it counts
Modern, fast, fully custom websites and web apps, designed and built end to end, to the same standard as everything else here. The site you're reading now is one of ours.
- Inputs: your brand, content, and goals
- Output: a polished, responsive site or web app you own outright
- Built in: performance, accessibility, and a clean handover
Every project is built around your workflow.
What's included, whatever we build.
An architecture you approve
A clear design covering data flow, integrations, model selection, and projected running costs, delivered before any build work begins.
A working system you own
The full codebase and deployment instructions. No black box, no per-seat license, no lock-in.
Verification built in
Where correctness matters, systems ship with checks that validate output before it reaches a human or customer.
Optional maintenance
A monthly retainer for prompt refinement, model upgrades, and source updates, available only if you want it.
The tools we build with.
Current frontier models and a pragmatic, boring-where-it-counts stack, chosen per project to fit your constraints and budget.
Not sure which fits your problem?
That's what the discovery call is for. Describe the workflow, and we'll map out the system we'd build for it.
Book a discovery call →Weekly intelligence pipeline for a commodity trading firm.
A full multi-agent AI system that turns an overwhelming stream of global sources into a verified, decision-ready briefing the firm's principals rely on every week.
The problem
A boutique commodity trading firm needed authoritative weekly intelligence across several volatile, specialized domains: Iraq, hard-banking jurisdictions, infrastructure, and emerging-market commodities. Their analysts were losing a significant share of every week to reading and hand-synthesizing a sprawling set of sources, with no consistent, decision-ready output.
The build
A full multi-agent AI pipeline. A triage layer distills a high-volume feed down to what matters. Domain-specialized agents produce structured analyses; a cross-cutting agent surfaces multi-domain events; a context layer adds logistics and conditions. A Writer composes the executive briefing, and a Verifier validates every claim against its source before dispatch, auto-revising anything unsupported.
The outcome
The briefing now goes out automatically every week, and the firm's principals act on what it surfaces. In one case it flagged a live opportunity they'd missed completely, exactly the kind of thing it's built to catch. It runs in production and clears its own claim-by-claim verification before every send.
Built on frontier Anthropic Claude models, Python orchestration, prompt-cached system prompts, automated dispatch, and live source sync. It is engineered to run autonomously at a fraction of the cost of the work it replaces.
Hundreds of sources, turned into one short weekly briefing.
How a build like this comes together.
The architecture didn't arrive fully formed. It's the product of a disciplined, repeatable process. Tap any stage to expand.
A single prompt can't reliably do an analyst's whole job. We break the work into discrete, testable stages: triage, domain analysis, cross-cutting synthesis, a scoped context layer, writing, and verification. Each agent has one job it can do well, and each can be measured and improved on its own.
Every stage is refined against real domain feedback, round after round, until its output converges on what an expert reader would accept. This is where most of the engineering time actually goes, and it's what separates a one-off demo from something a team relies on every week.
A dedicated verification stage checks every claim against its source before anything is sent. If a claim isn't supported, the system revises itself and tries again rather than shipping it. Correctness is built into the pipeline, not left to a manual final read.
The system is built to run unattended on a schedule, with matched models, cached prompts, an archive of every source, and automated dispatch, so it performs reliably week after week at a sensible running cost, not just once in a demo.
Have a repetitive process that eats your team's hours?
Chronos is one example of what a custom build can do. Tell us about your workflow on a free 15-minute call, and we'll show you what we'd build for it.
Book a discovery call →Most businesses don't need another AI subscription.
They need a specific, repetitive, expensive problem solved: the report that takes two days to compile, the inbox that needs triaging, the documents nobody has time to read carefully. Off-the-shelf tools are built for the average version of those problems, so they rarely fit the version you actually have.
We were founded on a simple premise: the highest-leverage AI work right now isn't buying a product. It's building the right system for one business's real workflow and handing over something they own outright.
Peter Adams
Founder & principal engineer
Every engagement is led by Peter directly, from the first discovery call through architecture, build, and handover. You are never handed to a junior team or an account manager; the person who scopes your problem is the person who builds the solution.
Computers have fascinated me for as long as I can remember. I built my first PC at 10, and when I found AI, what got me was how much it could do for anyone willing to actually put it to work. That's why I started Etapplied: to help businesses take a real, expensive problem and solve it with a custom AI tool they own.
Three principles behind every build.
Principal-built
Architected and shipped by a senior engineer, not delegated to generalists. Faster decisions, no telephone game.
Iteration-driven
Multiple cycles of expert review before convergence. The system you receive is tested against your domain's real edge cases.
Built for production
Not a flashy demo. Systems ship with verification and monitoring built in, engineered to run reliably and unattended, week after week.
Four stages, fully transparent.
We talk through the problem and map out what we'd build to solve it: the approach, what it connects to, and roughly what it would take. It's a relaxed, no-commitment call, and you leave with a clear picture of the system and the next step.
Architecture, data flow, integrations, model selection, and cost projections, all laid out so you can see exactly what will be built, how it fits your systems, and what it will cost to run. Nothing proceeds until you've approved the design and the budget.
Custom development with iteration cycles built in, so the timeline scales with the size of the system. You review interim output and your feedback shapes each round, so you're never waiting in the dark, and we keep going until it meets your acceptance criteria.
You receive the codebase, knowledge files, and deployment instructions, and the system runs on your own accounts and infrastructure, so you're never locked in. Ongoing upkeep (prompt refinement, model upgrades, source updates) is an optional retainer, not a dependency.
Before you book a call.
It depends on scope, which the design stage establishes; a focused automation and a full multi-agent pipeline are very different builds. Engagements are quoted as a fixed build cost (not hourly), with an optional monthly maintenance retainer, and you approve the number before any build work begins. Once live, running costs are typically a small fraction of the human hours the system replaces.
Build time is proportional to scope; a single automation ships faster than a full multi-agent pipeline. We set a realistic timeline together during design, and you see working output along the way rather than waiting until the end.
Yes, entirely. At handover you receive the full codebase, the knowledge files, and deployment instructions. The system runs on your infrastructure and accounts, with no per-seat license and no lock-in.
Yes. What we build plugs into the systems you already run, your data sources, email, Slack, Drive, and the rest, so it fits around your stack instead of the other way around.
Let's map out your build.
A 15-minute discovery call is free and low-commitment. You'll leave with a clear plan for what we'd build and what it would take.
Book a discovery call →Or send a note
A sentence or two about the workflow you'd like to automate is plenty to get started.
The discovery call, in plain terms.
Fifteen minutes
Short and focused. You describe the workflow, and we ask the questions that get to a concrete plan.
No cost, no pressure
The call is free and relaxed. You'll walk away with a concrete idea of what we'd build for you.
A clear next step
You'll leave knowing exactly what we'd build first and what a realistic first version looks like.