Engineering, QA, and AI teams that plug into yours

Peaksoft is a technology consultancy. We place senior AI, QA, DevOps, and software engineers directly on client teams — remote or onsite — for engagements that run from a few weeks to a few years.

01

AI Engineering & AI QA

LLM features built to spec, and evaluation suites that prove they work.

02

QA Automation

Test frameworks, CI integration, and coverage your team will maintain.

03

DevOps & Cloud

Deployment pipelines, infrastructure as code, and real observability.

04

Software Engineering

Full-stack delivery, architecture work, and legacy modernization.

AI work, handled like engineering

Most AI projects fail in the same place: a demo works, then nobody can say whether the next prompt change made it better or worse. We staff both sides of that problem — engineers who build the feature, and QA engineers who make its behavior measurable.

Model output is testable behavior, not magic. We treat it that way from the first week of an engagement.

What we don't do

We don't train foundation models, and we'll tell you when a problem doesn't need AI at all. Most of our AI work is applied engineering on top of existing models — that's where the cost and reliability problems actually live.

AI Engineers

Building the feature

  • LLM feature design: chat, search, summarization, extraction, classification
  • Retrieval pipelines — chunking strategy, embeddings, vector store selection, retrieval tuning
  • Model selection with cost, latency, and accuracy tradeoffs documented
  • Guardrails, fallback paths, and graceful failure when the model gets it wrong
  • Prompt and model version management, deployment, and production monitoring

AI QA Engineers

Proving it works

  • Evaluation suites scoring accuracy, grounding, format compliance, and tone
  • Golden datasets and regression baselines for every prompt and model change
  • Automated eval runs in CI, so a prompt edit is reviewed like a code change
  • Adversarial testing for prompt injection, data leakage, and unsafe output
  • Human-in-the-loop review workflows with defined scoring rubrics

Core services

Four areas where we place consultants. Every engagement is scoped to your stack, your team, and your timeline — not a fixed package.

01

AI Engineering & AI QA

AI engineers who ship LLM-backed features, and AI QA engineers who build the evaluation and regression testing that keeps them honest.

  • LLM integration
  • RAG pipelines
  • Prompt engineering
  • Evaluation & scoring
  • AI-assisted test automation
  • Guardrails & red-teaming
02

QA Automation

Automation frameworks and testing strategy that shorten regression cycles without becoming a maintenance burden for your team.

  • Test automation frameworks
  • CI/CD integration
  • Performance testing
  • API testing
  • Mobile testing
  • Test strategy & coaching
03

DevOps & Cloud Engineering

Infrastructure and deployment pipelines that scale with your team, with monitoring that tells you something useful when it breaks.

  • Infrastructure as code
  • Container orchestration
  • Cloud migration
  • Monitoring & observability
  • CI/CD pipelines
  • Security & compliance
04

Software Engineering

Full-stack engineers who can ship features, untangle legacy systems, and leave your codebase better documented than they found it.

  • Full-stack development
  • Architecture & design
  • Code review & optimization
  • Legacy modernization
  • API development
  • Technical leadership

Why teams work with Peaksoft

Clear scope, senior engineers, and regular communication. That's most of it.

01

Fast to start

Most engagements begin within one to two weeks of the first call. We send real consultant profiles, not a generic capabilities deck.

02

Senior consultants only

Every engineer we place has shipped and supported production systems. You interview them before they join, same as a direct hire.

03

Outcome-focused

We agree on what success looks like before the engagement starts, then review it on a regular cadence and adjust when it isn't working.

04

Flexible terms

Start with a short engagement to evaluate fit. Scale the team up or down month to month as your roadmap and budget change.

How engagements work

We keep the process simple so you can spend your attention on the project instead of managing a vendor.

01

Direct access to your consultants

No account manager sitting between you and the engineers. You talk to the people doing the work, in your Slack and your standups.

02

Adjustable team size

Add or reduce consultants month to month. We'd rather scale down honestly than bill for people you no longer need.

03

Written updates, not status theater

A short weekly summary of what shipped, what's blocked, and what changed — so you can forward it instead of translating it.

Engagement models

Team augmentation
Consultants embedded in your team, billed monthly per engineer.
Ongoing capacity gaps
Project delivery
Defined scope, milestones, and acceptance criteria agreed up front.
Discrete, well-bounded builds
Fractional leadership
A part-time architect, QA lead, or AI lead for a set number of days.
Teams missing a senior voice
Assessment
A two to four week audit ending in written findings and a plan.
Before committing to a direction

Industries we've worked in

SaaSHealthcare TechFinTechLogisticsE-commerceEnterprise IT

Ready to talk about your project?

Tell us what you're building. We'll tell you honestly whether we're the right fit and what a first engagement would look like.

Office

2800 S River Rd, Suite 450
Des Plaines, IL 60656