01 / Discover
A week inside the workflow: which steps eat hours, which decisions need a person, and which data an agent can trust. You get a written map and a fixed quote before anything is built.
AI agents and software engineering
Velantis designs and ships agents and software for B2B teams, at a fixed scope and a clear price.
01 / Discover
A week inside the workflow: which steps eat hours, which decisions need a person, and which data an agent can trust. You get a written map and a fixed quote before anything is built.
02 / Build
The agent is wired into the systems you already use — inbox, CRM, spreadsheets, your own APIs — with every action logged and every risky step held for approval.
03 / Run
Once live, every run is watched: what it did, what it cost, where it needed a human. We catch drift before you do, and the code, prompts and accounts stay yours.
Services
Most engagements start with an agent and end up touching all three. One team, one fixed scope, one price.
Agents that take repetitive work off your team.
Products and internal tools people actually use.
The plumbing that keeps everything reliable.
Agent demos
Press run and follow each step: what it reads, which tools it uses, and where it stops for your approval. These are recorded runs on sample data, so nothing you do here is sent anywhere.
A shipper emails a messy quote request. The agent reads it, checks rates and capacity, prices it with your margin rules, and drafts the reply for you to approve.
Steps
Action log
Readyquotes@ inbox
InboxQuote: 2 pallets Chicago to Dallas, need by Fri
NewDana Ortiz · Brightline Furniture
Customs docs for SHP-2291
WaitingOps · Harbor & Pine
Re: invoice copy please
DoneM. Chen · Lakeside Goods
More detail on each run, and what it would take to build one for you, on the demos page.
GPU routing · interactive demo
Run a simulated inference router: switch policies, fail a pool, spike spot prices, and watch every decision and its reason.
Simulated environment. Prices and latencies are illustrative.
ROI calculator
Put in your own numbers. Everything is worked out in your browser and nothing is stored.
At 400 tasks a month, an agent handling 60% would save about 48 hours, roughly $1,680 a month. A Starter Agent would pay for itself in 3.6 months.
Estimates only. Real savings depend on how much of the work an agent can safely take on, which the Agent Audit measures.
Process
The same path for every build, so you always know what happens next and what it costs.
01
Map the workflow, the data and the decisions. Agree the scope and the price.
02
Set up access to the systems the agent needs, with the least permission that works.
03
A working agent on real cases within days, so you judge the work, not a slide.
04
Tests, guardrails, approval steps, logging and what happens when things fail.
05
Run it alongside your team on live work and measure it against how things were.
06
Go live, watch every run, and keep improving it — or take it over yourselves.
Work
Case studies go here as engagements finish — the problem, what we built, and what changed, with numbers only when they are measured.
Replace with a real engagement: the problem, what we built, and what changed.
Result: to be measured
Replace with a real engagement: the problem, what we built, and what changed.
Result: to be measured
Replace with a real engagement: the problem, what we built, and what changed.
Result: to be measured
FAQ
Every engagement is a fixed price agreed before work starts. Packages start at the prices shown on this site; the Agent Audit turns your workflow into an exact quote. No hourly billing and no surprise invoices.
An Agent Audit takes about a week. A Starter Agent is typically 3 to 5 weeks from kickoff to production, and a Production Agent 6 to 10 weeks, depending on how many systems it has to work with.
You do. The code lives in your repository, the cloud and AI provider accounts are in your name, and you get documentation when we hand over. You can run it yourselves or with us.
An agent only gets access to the data its workflow needs. Where we can, everything runs in your own accounts. We do not use your data to train models, and we are happy to sign your NDA and data processing terms.
Whichever fits the job — usually a frontier model through its API, with a smaller, cheaper one where it does the work just as well. Nothing ties you to a single provider.
Risky actions wait for a person to approve them, every action is logged, and anything the agent is unsure about is handed to your team instead of guessed. Mistakes become test cases so they are not repeated.
We agree the measures during Discover — usually time per task, volume handled, error rate and how often a person had to step in — and compare them with how things were before, during the pilot.
Your choice. We can monitor and improve the agent each month, or hand everything over with documentation and a walkthrough so your team runs it.
No. We need someone who knows the workflow well and someone who can approve access to the systems involved. We handle the rest.
We have offices in Hyderabad, Delhi and Virginia and work with B2B teams across time zones. Our agents are built for freight, travel, legal and professional services work.
Next step
A 30-minute call with the engineers who would build it. You leave with an honest view of what an agent can take on, and what it would cost.