200+ AI engineers between your roadmap and production.
For US SaaS and tech companies, we are the AI engineering partner for agents, RAG, evals and MLOps, taking AI from prototype to reliable production with dedicated squads embedded in your team, ramped in five business days.
The gap between your AI story and your AI system
AI roles stay open for months
LLM and agent engineers are scarce and expensive while your roadmap, customers and product timelines wait.
POC works, production doesn't
The demo impressed everyone; inaccurate outputs, latency, missing evals and silent failures make reliable production harder.
Inference costs scale with usage
Every new customer makes the agent loop more expensive. Without model routing and optimization, inference costs can quickly add up as you grow.
Production AI engineering, embedded in your team
SAS-01
Agent engineering & workflow redesign
Multi-step agents with tool use, MCP integrations and orchestration, with workflow redesign that helps turn them into reliable, useful systems.
SAS-02
RAG & retrieval systems
Retrieval pipelines, vector search and evaluation frameworks built for production reliability, permissioning and data freshness.
SAS-03
LLMOps & AI reliability
Evals, regression suites, monitoring, guardrails and audit logging as a continuous practice to maintain AI reliability after launch.
SAS-04
AI cost optimization
Multi-model routing, caching and small-model substitution that can reduce inference spend for teams already running AI in production.
SAS-05
Dedicated AI squads
3–10 engineers with LLM, RAG and MLOps experience working with your stack, standups and roadmap, with frontend, backend and cloud engineering alongside AI.
SAS-06
Compliance-ready AI for regulated verticals
SOC 2 and HIPAA-aligned engineering, audit trails and private or self-hosted model deployment for regulated HealthTech, FinTech and LegalTech products.
Ramped in 5 days
Hand-picked squads join your team within five business days and ship in two-week sprints — AI velocity without a six-month hiring cycle, and without gambling your margins on unoptimized inference.
Put an AI squad on your roadmap this month
Start with a free 30-minute assessment — you leave with a roadmap either way.
Frequently Asked Questions
What AI engineering services do SaaS companies typically need?
SaaS companies can use AI engineering for agents, RAG, LLMOps, AI integrations, evaluation systems and cost optimization.
How can SaaS companies move an AI proof of concept into production?
Production AI requires more than a working demo. Evaluation, monitoring, guardrails, integrations and reliable deployment help make the system ready for real users.
Can an AI engineering team work with an existing SaaS product team?
Yes. Dedicated AI engineers can work within your existing tech stack, development process and roadmap alongside your product and engineering teams.
How can SaaS companies reduce the cost of AI features as usage grows?
Model routing, caching and smaller models can help control inference costs as more customers start using AI features.