Side builds the AI feature and wires it into the systems you already run. Chat interfaces, document extraction, agent workflows, on-prem deployments when the data shouldn't leave your network. Useful, tested, and maintainable by your team once we hand it off.
We're software engineers who use AI well, not an AI research shop. These are the shapes we actually build.
Conversational interfaces grafted into the software your team already uses. Ask questions of your database in plain English. Talk to your SOPs. Query the historian without writing a SQL statement. Scoped to the right users, wired to the right data.
Pull structured data out of PDFs, scanned forms, credentials, and batch records using vision models plus deterministic post-processing. We built exactly this for a charter aviation client to replace a dispatcher's manual document review.
Multi-step automation that reads, decides, and acts inside your existing tools. Classify incoming documents, triage alarms, draft work orders, route tickets. Agents that know when to ask a human.
When the data shouldn't leave your network, we run local models on hardware that sits inside your environment. Cloud models when it makes sense, local models when privacy or latency demand it, both when the job calls for a mix.
Reusable, composable skills that slot into agent workflows. A skill to ask a database a question in natural language. A skill to extract data from a document. A skill to check the historian for recent values. We build the skill, you reuse it wherever it fits.
Model Context Protocol servers that sit between the model and your data, tools, and systems. We build custom MCP servers that know how to talk to your specific databases, historians, document stores, and line-of-business applications. The model calls the MCP server's API, the server translates it into the right query or action, and returns the result back to the model in a way it can understand.
Short loop. Ship a working slice early, then let it pull the rest of the work behind it.
One to two weeks. We read the code, talk to the people who'd actually use the feature, and pick the one slice where AI moves the needle for the least risk.
Four to six weeks. A production slice behind a feature flag, tied into your real systems, and usable by a small group before it goes broad.
Docs, runbooks, architecture diagrams, and a handoff workshop. You get the keys and the map. We stay on the phone for a year after.
Models get swapped as the landscape shifts. The opinions live in the integration work: how data flows in, how output gets validated, how the feature stays maintainable after we hand it off.
// One agent, your systems, our guardrails. import { Agent, tool, guard } from "@side/runtime"; import { historian, erp, workOrders } from "./tools"; export const alarmTriage = new Agent({ model: "router:auto", // fallback ladder tools: [historian, erp, workOrders], guardrails: [ guard.noPII(), guard.scope("plant"), guard.budget({ usd: 0.04 }), ], evals: "./evals/alarm-triage.yaml", }); await alarmTriage.run(alarm); // → classified · routed · logged · billed
Names redacted where needed. These are the shapes customers ask for first, across aviation, manufacturing, and general business software.
Built for a charter aviation client. A vision model pulls certifications, ratings, and expiration dates from pilot credential PDFs that used to take a dispatcher most of a morning. Human reviews the output, approves, done.
Ask a database or historian a question in plain English and get a cited answer. Useful for supervisors, analysts, and anyone who shouldn't have to write SQL just to check a number.
Incoming documents get classified, data gets extracted, and the right people get pinged. Humans only see what needs their eyes on it.
End-of-shift or end-of-day summaries assembled from operational data, alarm logs, and notes. Dropped into Teams, email, or wherever your team reads.
Classify incoming alarms using historical context and past resolutions. Route to the right team with a suggested response. Escalate cleanly when the model isn't confident.
Tell us about the workflow or feature you're thinking about. We'll come back with an honest scope, a working slice in weeks, and a clear picture of what it'll cost to run.