Agentic Operations
Run a live business process from start to finish, with AI agents doing the work and a person signing off.
VERACITY AI PODS
AI that does real work inside your business.
An AI Pod is a small team of our experts working with AI agents, embedded in your business to take on real work. Month-to-month, using the tools you already have.
What is an AI Pod?
A small team that works inside your business.
Who is on it
2 to 5 people, with at least an AI engineer or developer plus a domain expert who speaks your business's language.
What it does
The team works with a fleet of AI agents inside your business. The agents do the work, and our people direct it and check it.
How you engage
Month-to-month, or an engagement of about six months. No big up-front commitment.
Your tools
We use the tools you already have, or recommend ones that fit. You are never locked in to one vendor.
Small on purpose
A good engineer working with AI can do the work of five to ten people. So a pod stays small, and you are not paying for a crowd.
Not intimidating
A small team working alongside your team day to day, learning your business. Assign someone of yours to work with the pod, and the skill grows in-house.
Boutique, not big consultancy
Senior people you can get on the phone, on a month-to-month basis. A pod costs far less than a big-consultancy engagement, with no large team billed by the hour.
Trusted by teams we've served over 20 years
01
The Shift
Everyone's tried AI. Execution is another matter.
01
Capability ≠ impact.
Most AI experiments never make it into day-to-day work, let alone show up in the numbers.
02
Trust is the blocker.
AI that nobody checks is AI nobody trusts with real work.
03
The old delivery model breaks.
When agents do the work, value no longer comes from billable hours or added headcount.
02The Model
AI Pods: experts and AI agents, working as one team.
A Veracity AI Pod is an embedded team of 2 to 5 people, with at least an AI engineer or developer plus a domain expert who speaks your business's language. They work with a fleet of AI agents inside your business. The agents do the work; our people direct it and check it. You pay month-to-month for a team that delivers, not for hours or seats.
Agents do the workExperts check itYou own the outputMonth-to-monthToken-meteredNo vendor lock-in
03
How It Works
Decide with evidence. No big-bang commitment.
Conversation
Find the right first job
Tell us where work is piling up. We'll say plainly whether a pod fits. If it helps, a short, paid AI Discovery Inception scopes it in detail.
Pilot
Prove it
We start a pod on real work and measure speed, quality, and cost against how it's done today.
Scale
Expand on results
Keep the pod going month-to-month, and extend it to other parts of the business as the results come in.
What a pilot looks like
Your AI research and development, on real work.
Q4 is pilot season. A pod started now is already doing real work when Q1 begins, and you plan the year with evidence instead of guesses.
- 01Pick one outcome
We start by asking what outcome you want to see, not just what you'd like built. Together we pick one real job: a process where work is piling up, or a prototype that needs to reach production.
- 02Land a small pod
A small team embedded with yours, working with you day to day on that job. It can be experimental too: if you think you know where to go, the pod helps you vet it and get there.
- 03Run it for a set term
Typically about six months, or month-to-month. Our pods running today are on six-month terms and month-to-month. No big up-front commitment.
- 04Measure, then decide
We measure speed, quality and cost against how the work is done today. Keep what works, trim what doesn't, and extend the pod to other parts of the business on the evidence.
04
The Pods
One pod model, configured for the job.
Every pod has the same shape: a small team plus AI agents. What changes is who is on it and what it works on. Here are some of the ways we configure pods. Pods are running today with software and insurance clients.
Agentic Product
Build AI-native products & copilots — new, or embedded into the apps you already run.
AI Engineering Enablement
Adopt AI coding tools, techniques, and workflows across your engineering teams — with standards and guardrails.
Vibe-to-Enterprise
Turn AI-built prototypes into tested, reliable production products.
AI Modernization
Move older systems onto modern platforms and get them ready for AI to work with.
Regulated Industries
Financial services and healthcare: AI-run operations with senior domain experts, audit trails, and compliance guardrails.
ComingSynthetic Operator — an always-on AI operations monitor & first-responder.
05
Proof
Pods are running today, on real work.
InsuranceStart-up carrier
Launching new product lines in days, not months.
~8 days
to launch a new insurance product line (it varies by line), where it used to take months
The problem
Every insurance product starts as industry-standard ISO forms: hundreds of pages of coverage questions, rate structures, premium calculations and underwriting rules. Keying them into a policy-administration system by hand takes months per line.
What the pod did
A pod embedded with a new carrier as its AI engine: AI strategy, software, and agents that read the ISO forms, map every element into the digital policy-administration platform, and check each output against the source before pod experts sign off.
Outcome
- New product lines live in about 8 days
- One repeatable process for every new line
- ISO structure preserved for state filings
SoftwareAI infrastructure product
A vibecoded prototype, industrialized into continuously verified production.
1,100+
spec-locked work units completed
The problem
AI makes a working prototype easy. Production is another matter: no specification, no tests, and no record of why the code does what it does. That is where most AI-built software stalls.
What the pod did
A pod running Veracity's agentic software factory. Every change starts from a written, locked spec; AI agents build in parallel, each in its own workspace; automated verification and an engineer's review come before anything lands.
Outcome
- Speed: agents work in parallel on spec-sized units
- Auditability: every line traces back to its spec
LegalHistorical records
Legal document transcription and collection for historical record purposes.
Viewable, searchable and queryable
a large collection of handwritten and legal documents, transcribed and preserved
The problem
A large collection of handwritten and legal documents existed only on paper and in scans: slow to read, impossible to search, and at risk of being lost.
What the pod did
A pod built a transcription pipeline in which AI reads each handwritten and typed document, organized the results into a structured collection, and published it as a private archive site.
Outcome
- Transcribed documents you can view, search and query
- Organized into a structured collection
- Preserved in a private archive site
Business operationsAdministration
An agentic chief of staff that manages administrative tasks within a business.
Daily action brief
that doesn't just list what's open: it takes on tasks itself, helps people finish theirs, and sends nudges to keep work moving
The problem
Administration spread across several mailboxes, calendars and business entities. Commitments live in inboxes, follow-ups slip, and hours go to triage instead of the work.
What the pod did
A pod built an agentic chief of staff: AI agents triage email across mailboxes and entities, manage the calendar and to-dos, take on admin tasks themselves, help people complete the ones still open, and send nudges so nothing stalls.
Outcome
- Tasks taken on and moved forward, not just listed
- Nudges that keep open work moving to done
- A person approves every outbound message
06
Why Veracity
We don't hand you agents. We drive results that move the needle.
01
Senior-led
US experts own the outcome and acceptance, not offshore ticket queues.
02
Governed by default
Audit trails, guardrails, and human sign-off engineered in from day one.
03
Model-agnostic
The best model for each task across Anthropic, OpenAI and 150+ more, plus your existing tools where they fit. No vendor lock-in.
04
Proven discipline
A spec-driven, continuously-verified delivery method, not slideware.
05
Regulated pedigree
Two decades in the industries where mistakes cost the most.
06
Prove it first
A paid pilot on your real work; you scale on evidence, not promises.
Model-agnostic across Anthropic, OpenAI and 150+ models, on our SOC 2 Type II and HIPAA-compliant platform.
SOC 2 Type IIHIPAA compliant150+ models
Veracity at a glance
- Years of software delivery
- 20+
- Clients served
- 300+
- Heritage
- FinServ &Healthcare
Partners and referrals
Know a business that could use a pod?
We work with advisors, consultants and business developers who introduce us to companies ready to put AI to work: teams buried in manual work, or sitting on a prototype they can't take to production. We have a referral program for partners, and we're always glad to hear from people who can advise or make introductions.
Start with a conversation.
Tell us where work is piling up. We'll tell you plainly whether a pod fits and what it would take on first. If it helps, we can then scope it in a short, paid AI Discovery Inception.