AltSlate Labs builds agent-first software. AI agents run the routine operations of your business; your people set the rules, supervise, and decide what matters.
Agents are the operating core. Your team directs them through dashboards and apps.
Illustrative · select an agent
See a platform built this wayEvery change waits for a person before it is applied.
Billing agent
Each agent reaches only the records its role allows.
Every action is on record. Sample
Want an opinion first?
Architecture Review
4–6 weeksKnow the pain, not the product?
Product & Customer Discovery
3+ monthsNeed the whole platform?
Full-Platform Partnership
or write to hello@altslate.com
You work with the founders, as one senior pod.Meet the team
AltSlate Labs builds and runs agent-first software for growing companies. AI agents carry out the routine operations of the business, and its people set the rules, supervise, and decide what matters. The same team builds real-time data platforms, rebuilds legacy systems, and trains compact language models, which is the engineering that agent-first software depends on.
Agent-first software is built around AI agents instead of adding an assistant to existing screens. In the systems AltSlate Labs builds, a supervisor routes each request to a specialist agent, and that agent does the work: scheduling, billing, customer conversations, reporting. The team directs the agents and sees what they did through dashboards and mobile apps.
An AI assistant or copilot helps one person work faster inside an existing screen, and that person still does the work. In agent-first software from AltSlate Labs, the agents do the routine work themselves, coordinate with one another, and hand to a person only what needs a decision. The gain is capacity for the whole team, not speed for one user.
You set the rules, and AltSlate Labs builds them in. For finance, accounting and regulated work, a person approves every change before it is applied. For day-to-day operations, agents act within set limits and send exceptions to a person. For marketing, outreach and sales, agents act and people review results. Each agent reaches only the data its role allows, and every action is recorded.
AI agents suit routine operational work that follows rules but still needs judgment: updating records, scheduling, handling customer chats and calls, preparing invoices, drafting documents and flagging exceptions. In one platform AltSlate Labs built, 41 agents work together and handle more than 80% of the client’s daily tasks.
Start with one problem. In a Quick Build of four to eight weeks, AltSlate Labs scopes one problem that costs your team time, builds the software that handles it, tests it with your team and hands it over running. Companies that want an outside opinion first can begin with a two-to-four-week Architecture Review. Timelines are fixed; team size flexes.
A first working result takes four to eight weeks with AltSlate Labs: one problem, scoped, built, tested with your team and running. A full platform with agents at its core takes three months or more and is delivered in increments you see every week. One client went from concept to paying customers on three continents in under twelve months.
Yes. Moving an AI pilot to production is the core of AltSlate Labs’ work. The team adds what a prototype lacks: guardrails, oversight rules, per-request cost tracking, infrastructure as code, zero-downtime releases, and monitoring. One client went from concept to paying users on three continents in under twelve months.
AltSlate Labs can. It operates the AI products it built for a consumer trust-and-safety company, which are live with paying users on three continents. A Full-Platform Partnership covers support, documentation, monitoring and enhancements. Clients who prefer to run the system themselves receive the documentation and a handover to do so.
Yes. AltSlate Labs trains compact language models from scratch. Its open Jugnu research family includes a 110M-parameter model scoring 81.25 on BLiMP and a 53M model ranked #3 on the sub-150M Tiny-ML Leaderboard. These are base research models; the same pretraining, fine-tuning, evaluation, and distillation skills go into custom models for clients.