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Velocity Tech Inc
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AI-first engineering · Dallas–Fort Worth

Most AI projects
die in the demo.
We build the ones
that ship.

An engineering consultancy built around AI. Grounded in your data, measured against real evaluations, handed over as software you own.

Book a discovery call How it goes
Bedford, TX Nationwide delivery Engagements from 2 weeks
tenant: acme-logistics
Grounded response
Customer
What's the penalty if we cancel a scheduled pickup inside 24 hours?
Assistant
Cancellations inside 24 hours are billed at 40% of the quoted rate. Cancellations made earlier are not charged. Weather-related cancellations are exempt under the force majeure clause.
terms_v4.pdf · §7.2 sla_2026.docx · §3
Retrieval pipeline
Embed & search 42ms
pgvector · scoped to tenant · top_k 8
Confidence gate 0.87
above threshold — proceeding
Generate + cite 1.1s
every claim mapped to a source
2 citations verified
Stack
Java Spring Boot AI / ML Angular Apache Spark Docker SQL MongoDB AWS Azure GCP Kubernetes Python React Node.js
Roles we place
Developer Software Engineer Data Engineer QA & Testing Business Analyst Workday Consultant
The gap

A demo is not a system.

Wiring a model to a prompt takes an afternoon. Everything after that is engineering — and it's where most projects quietly stall.

indexed sources · 4,182 chunks
SourceTypeChunksFreshness
terms_v4.pdfContract3122h
sla_2026.docxPolicy882h
zendesk_exportTickets3,10414m
ops_handbookInternal5411d
pricing_sheetCommercial1376h
Built in-house

We run our own business on this.

Velocity is a consultancy and a recruitment agency. The AI running both is software we wrote ourselves — which is where the practice comes from, and why we're careful about what we promise.

Talent Pipeline

Jobs, candidates, scheduling and prep in one place. It runs our own recruitment desk.

The challenge

A single req sprawls across four tools — postings in one, resumes in a mailbox, interviews in a calendar, prep notes in somebody's head. Nothing reconciles, and the strongest candidate accepts elsewhere while you're still trying to find a slot.

What it does about it
  • Tracks every opening in one place, and pulls matching roles off job boards on a schedule
  • Reads and scores each applicant against the actual requirement, with its reasoning shown
  • Books the interview and keeps the whole panel in sync
  • Writes the prep sheet — background, gaps, questions to ask — before the call
Senior Data Engineer · open 9 days
312
Applied
48
Screened
12
Interview
3
Offer
D. Osei
Airflow, dbt, Snowflake · 7 yrs
94
M. Halvorsen
Spark, Kafka · 9 yrs
88
J. Whitfield
No pipeline experience
22
D. Osei · technical round THU 14:00
Panel: R. Mehta, S. Delgado · 60 min
Prep sheet drafted from CV and job spec ready
The engagement

What actually happens, week by week.

Three acts, roughly twelve weeks. You can stop at the end of any of them and keep everything produced so far.

WEEKS 1–2 Discovery

We start where the work happens.

Not in a workshop. We sit with the people doing the job — the agents answering the same ticket forty times a week, the clerk re-keying invoices into two systems. We count the volume, sample the hard cases, and ask what a wrong answer actually costs you.

More often than not, what arrives labelled as an AI problem turns out to be three process problems and one AI problem. Knowing which is which before you spend anything is the whole point of this phase.

What you get

  • Workflow map and volume baseline
  • Opportunities ranked by payoff and risk
  • Indicative cost and timeline per option
  • A written recommendation — including what to skip

Stop here and you keep the analysis. Some clients do, and go build it themselves. That's a fine outcome.

WEEKS 3–6 Prototype

We prove it on your data, not a sandbox.

Before we tune a single prompt, we build the evaluation set — a few hundred real questions with known-good answers, drawn from cases your team has already argued about. From that point on, "better" has a number attached to it instead of an opinion.

The prototype goes in front of the people who'd actually use it in week four, not week twelve. What comes back reshapes the scope more than any planning meeting ever has.

What you get

  • Working prototype on your real data
  • Evaluation set and baseline scores
  • Retrieval and grounding layer
  • An honest read on what it can't do yet

Stop here and you keep the prototype, the eval set and the source. All of it runs in your cloud.

WEEKS 7–12 Production

We make it safe to put in front of customers.

The distance between a convincing prototype and something you'd let a customer touch is guardrails, access control, PII handling, audit logging, cost and latency budgets, and a considered answer for when the model should decline to answer at all.

This is most of the engineering, and it's the part that gets skipped — which is why so much AI work stalls at the demo. Afterwards it either runs under our operation, or we hand it over with documentation and training and you own it outright. We'd rather you didn't need us.

What you get

  • Hardened, access-controlled deployment
  • Monitoring, budgets and drift alerts
  • Security review and operational runbook
  • Handover documentation and team training

Or keep going. We run it, watch the drift, and iterate as your data changes.

What we do

AI at the centre. Engineering all around it.

AI & LLM engineering

Retrieval assistants, agentic workflows and structured extraction — with evals and guardrails.

RAGAgentsEvals

Document automation

Contracts, invoices and claims into structured data — with confidence scores and a review queue.

OCRExtraction

Custom software

Web platforms, internal tools and APIs, built by engineers who use AI throughout the process.

WebAPIs

Data & platform

Pipelines, warehouses and vector stores — the groundwork every AI system depends on.

PipelinesCloud

Staff augmentation

Vetted, AI-fluent engineers embedded in your team — introduced in days, not weeks.

ContractC2H

Enterprise solutions

Velocity ERP for operations past spreadsheets, plus security compliance assessments.

ERPCompliance
AI-augmented delivery

We don't just build with AI. We build using it.

AI tooling runs through our own process — which is why a small senior team covers ground that used to need a much larger one.

  • A named engineer signs off. AI accelerates the work; it doesn't approve it.
  • Your code stays yours. Your repos, your policies. No client code trains a model.
  • Faster feedback. Scope gets settled by evidence, not meetings.
sprint 14 · delivery log
ChangeReviewerTestsState
Tenant isolation on searchR. Mehta42/42merged
Citation span mappingA. Okafor18/18merged
Confidence threshold tuningR. Mehta31/31merged
PII redaction in logsS. Delgado9/11in review

Want a second opinion?

Thirty minutes with an engineer, not a salesperson. Bring the workflow you're trying to fix and we'll tell you honestly whether AI is the right tool.

Book a discovery call +1 682-254-6155
Get in touch

Let's talk.

Tell us about the problem. We reply within one business day.