Service

AI Solutions

Applied AI — RAG, agents, fine-tuning, and evaluation pipelines.

Overview

What it is.

Our Applied AI practice ships LLM-powered systems into production for regulated industries. We focus on reliability, observability, and the boring infrastructure that makes AI systems actually work at scale.

We build retrieval pipelines, agentic workflows, evaluation harnesses, and the safety guardrails that enterprise customers require.

Benefits

What you get.

✓
Production RAG systems with sub-second latency at scale
✓
Evaluation harnesses that catch regressions before users do
✓
Safety guardrails aligned to your regulatory regime
✓
Cost-aware model selection (OpenAI, Anthropic, open-source)

Process

How we run it.

01
Use-case scoping with measurable success criteria
02
Architecture design covering model, retrieval, and safety
03
Production pilot with weekly evaluation reports
04
Scale-out with cost and latency SLOs

Deliverables

What you walk away with.

Deliverable
Working AI system in production with observability
Deliverable
Evaluation dataset and regression tests
Deliverable
Cost and latency dashboards
Deliverable
Operational runbook for model updates and incidents

FAQ

Common questions.

How do you staff engagements?

Every Aightifier on your engagement has 6+ years of production experience. We don't use staff augmentation, junior developers, or offshore teams. Each engagement is staffed by 2-6 senior engineers with a dedicated engagement lead, and we add specialists as the work demands.

What does pricing look like?

We charge a flat monthly fee tied to the team size and engagement length. Typical engagements start at $45k/month for a two-engineer pod and scale based on scope. Pricing is benchmarked against top-tier consultancies and reviewed annually. We share OKRs and back them with skin in the game.

How long is a typical engagement?

Our average engagement is 28 months. The shortest engagements we accept are two-week paid pilots, and the longest client relationships have spanned seven years. We optimise for continuity, not headcount, which is why retention is our primary metric.

Do you sign NDAs and DPAs?

Yes. We sign mutual NDAs before discovery calls and execute enterprise DPAs as part of contracting. For regulated clients (HIPAA, GDPR, CCPA), we will work with your legal team to align on data residency, sub-processor lists, and breach notification timelines.

What is your security posture?

We are SOC 2 Type II certified, with annual audits by an independent firm. Our engineers are trained on secure-by-default patterns, and our delivery process embeds security reviews at every stage. For FedRAMP-bound workloads, we operate in GovCloud and maintain continuous monitoring controls.

Can you work with our internal teams?

Yes — and we prefer it. The most successful engagements pair our engineers with your engineers on shared goals. We use your tooling where it makes sense, document our decisions in your wikis, and aim to leave your team stronger than we found them.

What happens after launch?

Every shipped system comes with a two-year defect warranty at no additional cost. After that, you can keep us on for managed services, hand off to your internal team with a knowledge-transfer plan, or a mix of both. We never hold systems hostage.

Do you work with startups?

We do, with one caveat: we are not the cheapest option, and we are not the right fit for pre-product-market-fit teams. We typically engage with startups that have found traction and need to scale production-grade systems without growing an internal team too quickly.

How do you handle AI safely?

Our AI practice is built around evaluation, observability, and guardrails. Every AI system we ship has an evaluation harness in CI, observability dashboards in production, and explicit guardrails for safety and compliance. We treat AI as a system component, not magic.

Ready to start AI Solutions?

Most engagements begin with a 30-minute intro call and a two-week paid pilot.

Start a project