Which roles can you provide?

GenAI and LLM engineers, ML engineers, data scientists, data engineers, MLOps engineers, backend and integration engineers, AI quality and evaluation engineers, product managers, conversation designers and solutions architects.

How do you choose the right mix?

We start from your goal and data. A prototype may need three roles. A production system with monitoring and compliance usually needs more. We recommend the smallest team that can ship safely.

What seniority levels are available?

Teams are mixed. A senior lead sets direction and review standards, with mid-level and junior engineers doing delivery under that guidance.

Do you work with our existing models and tools?

Yes. We work in your cloud, repositories and toolchain, and we are comfortable with both proprietary and open-source models.

Can the team include our own staff?

Absolutely. Many squads are blended, with your engineers or product owner embedded alongside ours.

How does the team communicate with us?

In your channels. Expect daily async updates, a weekly demo and a monthly steering review.

What time zones do you cover?

We plan overlap hours with your team up front. Most clients agree a core window of three to four shared hours.

How is work planned and tracked?

In sprints, in your project tracker. You see the backlog, priorities and progress at all times.

Who owns delivery decisions?

You own priorities and product decisions. The squad leads on engineering choices and flags trade-offs clearly.

How do you handle knowledge transfer?

Documentation, runbooks and recorded demos are part of the definition of done, so your team can take over whenever you decide.

Who owns the code and models?

You do. Work is delivered into your repositories and cloud accounts, and IP is assigned to you under the contract.

How is our data protected?

Access is least-privilege and logged, work happens in your environment where possible, and every team member is bound by confidentiality terms.

Can you work inside our secure environment?

Yes. We can work through your VPN, virtual desktops or private cloud, following your security policies.

Is our data used to train other models?

No. Your data is not used to train models for anyone else.

Can you support compliance requirements?

We design with privacy and auditability in mind and work with your compliance team on regulated use cases. Specific certifications depend on your requirements.

How is pricing structured?

Typically a monthly rate per role, based on seniority and effort. You receive a clear estimate with the squad proposal.

How quickly can the team start?

Often within one to two weeks of agreeing scope, depending on the roles needed.

Is there a minimum commitment?

We prefer an initial engagement of a few months so the squad can deliver something meaningful, with flexible notice afterwards.

Can we scale the team up or down?

Yes. Roles can be added or released with reasonable notice as priorities change.

How do we measure value?

We agree success metrics up front, such as time to release, model quality and business impact, and report on them every sprint.

AI Teams

The AI team you need, shipping in days

Aarvexa assembles dedicated squads of ML, GenAI, data and MLOps specialists that plug into your product, your tools and your roadmap, and deliver working AI from the very first sprint.

Dedicated squads
Ready in about a week
You own the IP

Build my AI team Compose a squad

Sprint 14 · Acme AI squadlive

6 specialists

Sprint done38%

BacklogIn progressReviewShipped

RAG re-rankerGenAI / LLM Engineer

Eval harnessAI Quality & Eval Engineer

Feature storeData Engineer

Canary deployMLOps Engineer

Prompt guardrailsGenAI / LLM Engineer

Churn model v2ML Engineer

Data contractsData Engineer

Demo scriptAI Product Manager

Velocity+38%

Models in prod3

Eval pass94%

Squad ready

In about 7 days

Next demo

Friday, 3 pm

Squad composer

Build the team you need, then see what it covers

Pick a starting point or add roles one by one. The panel shows headcount, skill coverage and how soon the squad can start. Estimates are indicative.

GenAI / LLM Engineer
RAG, agents, prompt and guardrail design, fine-tuning.
1
ML Engineer
Training pipelines, model selection, serving and optimisation.
0
Data Scientist
Problem framing, experiments, features and statistical rigor.
0
Data Engineer
Pipelines, warehouses, data contracts and quality checks.
1
MLOps Engineer
CI/CD for models, monitoring, drift alerts, cost control.
0
Backend / Integration Engineer
APIs, event flows and wiring AI into your existing systems.
1
AI Quality & Eval Engineer
Golden sets, red-teaming, regression suites, release gates.
0
AI Product Manager
Roadmap, success metrics, stakeholder demos and priorities.
1
Conversation & UX Designer
Flows, tone, fallback design and human-in-the-loop UX.
0
AI Solutions Architect
Reference architecture, security, scale and vendor choices.
0

Onboarding

From first call to production in thirty days

A clear path, with something to show at every step.

Day 0
Discovery call
We learn your goals, constraints and what success looks like in numbers.
Day 2
Squad proposal
You receive a role-by-role team plan with seniority, effort and working agreements.
Day 5
Access & setup
Repos, environments, security review and shared channels are ready.
Day 7
Sprint one starts
Backlog agreed, definition of done written, evaluation plan in place.
Day 14
First demo
A working slice running in your environment, with measured results.
Day 30
Production slice
First release behind a flag, with monitoring, alerts and a runbook.

Operating rhythm

A delivery rhythm your stakeholders can set a watch by

Every sprint follows the same five beats, so progress is visible and surprises are rare.

Step 1 of 5Plan

Start of each sprint

Plan

Goals, scope and capacity are agreed with your product owner. Risks are named early.

You getSprint goal and backlog

Toolbelt

Fluent in the tools your stack already uses

We adapt to your cloud, models and pipelines. Tool names below are examples, not endorsements or affiliations.

Models & GenAIClaudeGPTLlamaMistralGeminiLangChainLlamaIndexDSPyvLLMHugging Face

Data & MLOpsAirflowdbtSparkKafkaMLflowKubeflowFeastWeights & BiasesDatabricksSnowflake

Cloud & deliveryAWSAzureGoogle CloudKubernetesTerraformGitHub ActionsDockerFastAPIDatadogGrafana

Squads in action

What a focused team can ship in weeks

Four illustrative engagements. Figures are examples of typical outcomes, not guarantees.

Retail marketplace41%of tickets resolved without an agent

Support copilot squad

A GenAI engineer, data engineer, QA lead, PM and backend engineer built a retrieval-based assistant on the help centre and order data.

5 specialists6 weeks to first release

Speed to value

Weeks to your first model in production

A typical comparison for a mid-sized use case. Real timelines vary with role mix, market and scope.

Hire in-house

Job posts, interviews, notice periods, onboarding.

26 wks

Freelancers, ad hoc

Finding, vetting, context lost between people.

14 wks

Aarvexa AI team

Squad ready in days, first release in weeks.

4 wks

Week 01326

Collaboration

Your squad lives in your channel

No separate portals. Updates, questions and demos happen where your team already works. A sample day, illustrative.

A shared channel
The squad lives in your Slack or Teams, not in a separate portal.
Daily async standup
Three lines a day: done, next, blocked. No meeting needed.
Weekly demo
Working software shown to your stakeholders every sprint.
Monthly steering
Metrics, spend and roadmap reviewed with your leadership.

# ai-squad-acme6 members

MeeraAI Product Manager09:02

Sprint 14 goal: ship the retrieval upgrade behind a flag. Demo is Friday at 3.

Message #ai-squad-acme

Working terms

Built to be low-risk to start and easy to change

Typical terms we offer. Final terms are set out in your agreement.

01
Swap guarantee
If a team member is not the right fit, we replace them, typically within two weeks.
Included
02
Your IP, your code
Everything the squad builds is assigned to you, in your repositories.
Included
03
Flex up or down
Add or release roles with about 30 days' notice as your needs change.
Included
04
Weekly transparency
Time, progress and spend reported every week, in plain language.
Included

FAQ

Frequently Asked Questions

Straight answers on hiring and working with a dedicated AI team: skills, security, cost and timelines.

An AI team is a dedicated group of specialists, such as ML engineers, data engineers, GenAI engineers, MLOps and QA, who work together on your AI roadmap as an extension of your own organisation.

A squad works to shared standards, knows your context across sprints and has the roles needed to ship, not just to prototype. If someone leaves, the squad's knowledge stays.

Product companies adding AI features, enterprises building AI platforms, and teams that need to move faster than recruiting allows.

Yes. Many clients begin with a small squad of three or four people on a single use case and expand once results are proven.

Book a free consultation. Within a couple of days you receive a squad proposal with roles, effort and a start date.

One seat is open

Your AI team is one conversation away

Tell us what you want to build. In a couple of days you will have a squad proposal with roles, effort and a start date, free and with no obligation.

Build my AI team Compose a squad

The AI team you need, shipping in days

Build the team you need, then see what it covers

GenAI / LLM Engineer

ML Engineer

Data Scientist

Data Engineer

MLOps Engineer

Backend / Integration Engineer

AI Quality & Eval Engineer

AI Product Manager

Conversation & UX Designer

AI Solutions Architect

From first call to production in thirty days

Discovery call

Squad proposal

Access & setup

Sprint one starts

First demo

Production slice

A delivery rhythm your stakeholders can set a watch by

Plan

Fluent in the tools your stack already uses

What a focused team can ship in weeks

Support copilot squad

Weeks to your first model in production

Hire in-house

Freelancers, ad hoc

Aarvexa AI team

Your squad lives in your channel

A shared channel

Daily async standup

Weekly demo

Monthly steering

Built to be low-risk to start and easy to change

Swap guarantee

Your IP, your code

Flex up or down

Weekly transparency

Frequently Asked Questions

Your AI team is one conversation away