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// AGENTIC AI DELIVERY TEAM

Ship production agentic systems in your stack in 4–6 weeks.

Scalac.ai is an embedded AI engineering team — we design, build, and ship production agentic systems inside your infrastructure.

For enterprises with complex workflows: deterministic orchestration, observability, and cost control from day one.
  • Production-ready from day one
  • Runs in your VPC
  • Traces, fallback, and budget controls built in
Book a 30-Minute Architecture Call - Free
Built on 10+ years of distributed systems engineering, including Akka-based, event-driven architectures.

Why production AI costs 3× more than the pricing page

The Real Cost of Running LLMs in Production

Download our whitepaper „The Real Cost of Running LLMs in Production” — 22 pages on hidden costs, model routing, retry architecture, and what production-ready teams do about invoice shock.

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    Why 80% of AI Pilots Never Reach Production

    Your Prototypes Work on Demo. Production Takes 8 Months.

    Your engineering team built three AI prototypes. Each demo impressed the board. None handle failure. None talk to each other. None survive past 5 PM.

    THE FIX

    Deterministic orchestration, full traceability, production SLAs, and failure-safe workflows — built in from day one.

    Your CFO Sees a $15,000 Surprise on the Invoice

    You built a PoC on the most expensive model. At 500K requests per month, your CFO sees a $15,000 surprise. Zero visibility into which model runs when, or why.

    THE FIX

    Intelligent model routing, tiered fallback, and cost attribution per agent. You control spend. You see exactly what costs what.

    How We Build Production Agentic Systems

    EXECUTION LAYER 01

    Architect Multi-Agent Coordination Inside Your Stack

    Your event-driven systems already move data and trigger workflows. We add an orchestration layer that plans, routes, verifies, and escalates tasks — without breaking your existing architecture.
    Multi-agent coordination with deterministic orchestration
    MCP-native integration layer — swap models without rewriting
    Eval harness from day one: traces, latency, cost, success

    Plan

    Route

    Verify

    Plan Route Verify Orchestrator alternates routing between fast model and reasoning model. request orchestrator models verifier output req plan route fast fast model reason reasoning verify done
    → routing: fast model
    AFTER 6 WEEKS
    TYPICAL APPROACH
    Still in discovery.
    NOT LIVE
    Workshops, planning & team ramp-up.
    No production system yet.
    SCALAC.AI
    Live in production.
    LIVE IN PRODUCTION
    Real users
    Measurable KPI’s
    System ready for next usecase
    EXECUTION LAYER 02

    A productized delivery team for production agentic systems.

    Two to three senior engineers act as your embedded AI delivery team, owning architecture, integration, and production readiness from day one. Agentic tooling increases delivery speed, but accountability stays with senior engineers who make the critical system decisions.
    Assessment → Fit Memo and production readiness check.
    Blueprint → scope, architecture, and delivery plan.
    Build → live workflows, observability, and KPI tracking.
    Retained → continuous expansion into new workflows
    Book a 30-Minute Architecture Call - Free

    Why SCALAC.AI?

    Engineering DNA built on 10+ years of distributed systems.
    Scalac.ai is the agentic AI delivery unit of Scalac.io

    Agentic Systems, Not Chatbots

    Plan → execute → verify. We build autonomous workflows with deterministic orchestration, fallback paths, and full auditability.

    Distributed Systems DNA

    Our AI delivery work is rooted in the same engineering discipline behind Akka-based, event-driven, production-critical systems.

    Your Infrastructure, Your Rules

    Agents run in your VPC with traceability, cost control, and compliance-ready operational visibility.
    Book a 30-Minute Architecture Call - Free

    CASE STUDY

    Verified Deployments

    LEGALTECH / RESEARCH AUTOMATION
    Lex-GPT.pl
    Challenge: Legal teams spent hours cross-referencing regulation databases.
    4h → 2.4h per regulation check
    Reduced regulation cross-referencing from 4 hours to 2.4 hours for a team of 8 legal analysts. Multi-agent assistant with hierarchical planning, retrieval, verification, and parallel execution.
    Read Case Study at Scalac.ai
    HRTECH / PRODUCTION AGENT
    Autonomous Recruiting Agent
    Challenge: Build an autonomous agent that searches multi-tenant databases and orchestrates sub-tasks across JVM, Rust, and TypeScript services.
    Live in production — 4-language stack
    MCP + ADK-Java + Pekko HTTP + Rust A2A orchestrator. Multi-tenancy enforced at infrastructure level, not by the model. Tenant isolation via Bearer token propagated through every layer.
    Read Case Study at Scalac.io

    FAQ

    Frequently Asked Questions by CTOs & VP Eng

    From architecture assessment to production deployment: 4–6 weeks for the first use case. We start with a 30-minute assessment to verify fit, then scope a fixed-price pilot around one measurable KPI.
    No. We integrate agentic AI directly into your existing distributed systems — Kafka, Kubernetes, event-driven architecture — through MCP. One team, one stack, one deployment pipeline. No separate Python silo.
    Intelligent model routing (cheap model by default, expensive model for complex tasks), tiered fallback, cost attribution per agent, and token budgets per tenant. Our whitepaper breaks down the full cost stack.
    Agents run in your VPC. Zero data egress. Full compliance with EU AI Act (high-risk: August 2027) and DORA (in force since January 2025). You own the code, prompts, eval data, and infrastructure.
    No. You own the system: code, orchestration logic, prompts, evaluation assets, and infrastructure configuration stay with you. We can stay on as your delivery team, but you are never locked into a proprietary platform.

    CASE STUDY

    Architecture Guides & Technical Briefs
    Deep dives into agentic AI infrastructure, cost control, and production scaling.

    Last Month in AI – May 2026

    May 2026 was a massive month for AI, marked by Google’s I/O developer conference, major hardware announcements ahead of Computex, and significant shifts in the open-source landscape.

    Read more →
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    REACH US

    Book a 30-Minute Architecture Call – Free
    In 30 minutes, we audit your stack for agentic fit, identify the highest-ROI first use case, and deliver a Production Readiness Memo within 48 hours. No pitch deck. Just engineering.
    Request your call