Your competitors are already using AI. Most of them are using it badly.
Silicognitive helps small and mid-sized businesses put AI to work on the boring, expensive
parts of their operation — without a data team, a seven-figure budget, or a two-year
roadmap. You don't need to lead your industry in AI. You need to stop falling behind it.
No pitch deck. No jargon. We'll tell you if AI isn't your problem.
Built by an operator30 years in technical program management — 20 of them at Microsoft and Amazon
Time to first resultWeeks, not quarters — pilots ship inside 30 days
Where we workAustin, Texas — on-site regionally, remote everywhere
Who this is for
The gap isn't technology. It's who has time to figure it out.
Enterprises have AI teams. Startups have engineers who live on the frontier.
Everyone in the middle is watching from the sidelines — reading the headlines,
paying for tools nobody uses, and quietly wondering how far ahead the competition
already is.
5 to 250 employees, with real revenue and real operational pain
No in-house AI team, and no appetite for hiring one
Staff already pasting company data into chatbots, unsupervised
A competitor who suddenly quotes faster, or answers customers at midnight
Most mid-market AI spending goes to the wrong place: a licence for every employee,
a chatbot on the website, a pilot that impressed a board and then quietly died.
The money moves; the work doesn't change.
The businesses pulling ahead did something less exciting. They picked two or three
processes that cost them real hours — quoting, intake, scheduling, claims, support
triage, document review — and rebuilt exactly those with AI in the loop. Then they
measured it.
That's the entire job. Silicognitive does it with you, in your systems, using your
data, and hands it back documented so your team can run it without us.
What we do
Four engagements. Each one ends with something running.
Start anywhere. Most clients start with the audit, because guessing which process to
automate is the most expensive mistake in this whole category.
012 weeks
AI Readiness Audit
We sit with your team, trace how work actually moves through the business, and come
back with a ranked list: what AI can take off your plate now, what's worth building,
and what you should leave alone. Written for owners, not engineers.
process mappingtool auditROI ranking
0230 days
Pilot Build
One process, one working system, one number that moves. We build it against your real
data and your real workflow — not a demo environment — so the decision to expand is
based on evidence instead of a vendor's promise.
scoped buildreal datameasured baseline
034–8 weeks
Automation & Integration
Turning the pilot into infrastructure: connected to your CRM, inbox, scheduler, or
line-of-business system; monitored; with a human checkpoint wherever a wrong answer
would cost you a customer.
CRM & ops systemshuman-in-the-loopmonitoring
04ongoing
Team Enablement & Guardrails
Your people are already using AI — the question is whether they're doing it well and
safely. Hands-on training in their actual jobs, plus a written policy covering what
goes into these tools and what never does.
role-based trainingusage policydata handling
How it works
Find it. Prove it. Then scale it.
A deliberate sequence — each step has to earn the next one. If step two doesn't produce
a number worth acting on, we say so and you stop.
Step 01 — Find
A week inside your operation
Interviews with the people doing the work, a look at the systems they fight with, and
an honest count of where the hours go. Deliverable: a ranked opportunity list with
effort and payoff on each line.
Step 02 — Prove
One pilot, thirty days
We build the highest-value item on that list and run it beside your existing process.
Deliverable: a working system and a before-and-after measurement you can take to your
partners or your board.
Step 03 — Scale
Handover, not dependency
Integration, documentation, and training your team on the thing they now own. Our goal
is that you don't need a monthly retainer to keep it alive.
Who you'll work with
You get the person who does the work.
Founder & PrincipalTobin Titus
30 yrsTechnical program management
20 yrsMicrosoft · Amazon
Track recordLarge-scale program delivery
FocusSMB & mid-market operations
BasedAustin, Texas
Thirty years running technical programs — twenty of them at Microsoft and Amazon,
delivering at a scale where a missed dependency costs millions and a vague requirement
costs a quarter. The discipline that makes programs that size work — scope it small,
measure it honestly, ship it, then expand — is exactly what's missing from most AI
projects, at any size.
Silicognitive exists because the tooling finally got good enough that a 30-person
company can get enterprise-grade leverage out of it. What's still missing is
someone to point it at the right problem and stay until it works.
If the honest answer is that AI won't help your business this year, you'll hear that
on the first call — not after an invoice.
Straight answers
The questions owners actually ask.
We're too small for this, aren't we?
Almost always the opposite. Small teams feel a recovered afternoon immediately, and
they can change a process in a week instead of a quarter. The floor isn't headcount —
it's whether you have a repetitive, rules-heavy process that eats real hours.
Is our data safe? We handle customer records.
Every engagement starts with where your data may and may not go. That means deployment
choices that keep sensitive records inside systems you control, contractual terms with
any vendor in the chain, and a written policy your staff can follow. It's the first
conversation, not an afterthought.
Are you here to replace our people?
No — and the projects that try usually fail. The work that pays off takes the parts of
a job nobody wanted (retyping, chasing, sorting, first-pass drafting) and gives your
team back the hours for the parts that actually need a human.
We already pay for AI tools nobody uses. Why is this different?
Because licences aren't adoption. A tool sitting next to someone's workflow gets
ignored; a tool built into it gets used. We start from your process and work backward
to the technology, which is the opposite of how most of those licences were sold.
What does an engagement cost?
It's scoped to the work, and you'll have a fixed number before anything starts. The
audit is deliberately small so you can find out whether there's anything worth doing
without committing to a build. Bring your situation to the call and you'll get a range
on the spot.
Next step
Thirty minutes. One process. A straight answer.
Tell me what part of your business is eating the most time. I'll tell you whether AI is
the fix, what it would take, and roughly what it would cost — on the call, at no charge.