From first principles to production.
AI systems engineered to rununattended, audited, and trusted.
Production grade automation and custom software for the problems no product solves, taken from first principles to production and engineered to run unattended, audited, and trusted at scale.
Built for teams in
The portfolio
3 offerings. One standard.
- 01Available
Custom AI Engineering
Your system, engineered from first principles
PricingFixed price per phase, from a paid discovery sprint. Book a call for a scoped quote.
Engagement · Build - 02Available
Extrovert AI
The AI CRM that works your pipeline for you
PricingSubscription, priced to your pipeline volume. Book a call for current plans.
Product · Revenue - 03In development
Sillage
The AI governance platform for teams who will be audited
PricingIn development. Design-partner pricing for early teams.
Platform · Governance
Architecture
Inside the engine.
Every Stallwart build, product or engagement, moves through the same four layers. That is why a governance guarantee in one system is a governance guarantee in all of them.
Systems
- Custom AI EngineeringRuns through Intelligence, Orchestration, Governance, Production.
- Extrovert AIRuns through Intelligence, Orchestration, Production.
- SillageRuns through Governance, Orchestration.
Stallwart engineering core
Every build, every engagement
- 01
Intelligence
Where a judgment is made
Models are selected and constrained for the decision at hand, and calibrated to report their own uncertainty rather than assert through it.
- 02
Orchestration
Where work is routed
State, retries, and sequencing. The layer that makes a system run unattended instead of needing a person to advance it.
- 03
Governance
Where limits are enforced
Policy expressed as runtime controls, not documentation. Approval gates, escalation paths, and an audit trail written as work happens.
- 04
Production
Where it meets reality
Observability, rollback, and load behavior. The difference between a system that demonstrated well and a system that is still correct on a Tuesday.
How we operate
The terms, before you ask for them.
Cost, duration, ownership, and the commitments underneath them, stated up front. Handing over the work should never mean handing over control.
Full detail on request
What you own
Everything.
Source, infrastructure as code, runbooks, and documentation. Yours to keep, with no lock-in.
What it costs
Fixed price per phase, approved up front. Never billed hourly.
How long it takes
Weeks, not months, with a committed build date.
Encrypted in transit and at rest
TLS 1.2 or higher in transit, AES-256 at rest. Keys stay server side.
Your data stays yours
Your data is never sold and never trains shared models.
Regional data handling
Your data stays resident in the region you choose.
Human override, always
Every action is logged and reversible, and any run can be paused.
When we say no.
We say no when off-the-shelf already solves it, or the spend cannot be justified.
Case studies
Where the work breaks.
Case studies and writing on how operations actually fail, and what holds instead.
Why AI pilots do not reach production
Most enterprise AI never ships. The reason is rarely the model. It is the 80 percent of the system the pilot was allowed to skip.
Custom AI Engineering6 minAI governance before the audit, not after
Most teams assemble AI governance the week a regulator, customer, or board asks. By then the finding is already written. The absence of an answer is the finding.
Sillage6 minSpeed to lead is not a metric. It is the whole funnel.
Most B2B teams treat lead response time as a reporting line. Structurally it decides how much of your pipeline you ever get to compete for.
Extrovert AI5 minCase study: cutting a mid market SaaS team's lead response to minutes
How automatic scoring and follow up change the arithmetic for a SaaS sales team drowning in undifferentiated inbound.
Extrovert AI6 min
The origin
The AI industry has a confidence problem, not a capability problem.
Arun founded Stallwart on a direct observation: systems get sold on how convincingly they perform in a controlled demo, and the gap between that and real-world reliability becomes someone else's problem the moment the invoice clears.
He built Stallwart to close that gap, engineering AI systems that report their own uncertainty instead of asserting through it, and that are built to be audited, not just believed.
A software engineer with roughly five years building production systems, and building with AI since well before it was the default.
Read the full story →In their words
What changes when the system carries it.
Illustrative accounts by role and sector. We publish named customer quotes when we have them and not before.
Reps closing, not chasing
We stopped losing leads to slow follow up the week we turned it on. The queue reviews itself now, so the team spends its day in conversations instead of assembling a list.
VP of SalesMid Market SaaS · Extrovert AI Scoring paid for itself
Scoring alone justified the whole thing. We finally know which leads are worth a call before we make it, which changed how we staff the week.
Head of GrowthB2B Agency · Extrovert AI Leverage without headcount
As a five person team we needed output, not more people. This gave us the follow up persistence of a company three times our size.
FounderSMB Software · Extrovert AI
From first principles to production.
Tell us what keeps
falling through.
Bring us the process that only works because someone remembers it. We'll show you which part a system can take over, and say so plainly if the answer is none of it.