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While 40% of agentic AI initiatives fail by 2027 due to poor governance and shallow expertise, Dyntyx Talent Bench gives you plug‑in AI specialists with proven delivery patterns.
Less time hunting and interviewing AI talent
Faster kickoff on AI roadmap and build work
Fewer failed pilots and rewrites
From request to vetted candidate shortlist
AI budgets are growing, but most teams are stuck in the same place: strategy decks, half‑built prototypes, and no reliable way to execute. Internal teams are overloaded, and generalist contractors lack the depth to ship production‑ready agents and automations.
Dyntyx solves this through a curated AI talent network—engineers, architects, and operators who specialize in real‑world AI systems, multi‑agent workflows, and governance‑ready implementations. You get people who know how to move from idea to production, not just prompts to slides.
“10 AI prompts won’t replace your 500/hour consultant—but the right AI specialist can.”
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Leaders report they have more AI ideas than they can possibly execute with their current team capacity—delivery, not ideation, is the constraint.
Companies struggle to hire staff who can design robust architectures, integrate with existing systems, and manage risk at scale.
Organizations walk away from AI projects because they can’t staff them quickly or confidently enough. Pipeline sits idle while competitors ship.
Place an embedded AI engineer into your team who builds, tests, and iterates on concrete use cases—RAG apps, agentic workflows, automations, and integrations with your existing stack.
When your product, ops, or data team outlines a high‑value AI opportunity, your Embedded Engineer turns that into a scoped solution, wires up models, tools, and APIs, and ships a working version in weeks—not quarters.
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Partner with an AI Architect who designs your end‑to‑end approach: model selection, data flows, observability, cost control, and governance patterns. They align stakeholders, choose platforms, and define reference architectures your team can execute against.
A typical engagement replaces months of “solution thrash” with a clear target architecture and implementation plan that multiple vendors and internal teams can follow.
Staff AI Ops specialists who build monitoring, evaluation, and governance guardrails around your models and agents—so you can scale AI without flying blind. They design metrics, test suites, escalation rules, and audit trails.
Instead of worrying about hallucinations, drift, or silent failures, your team gets dashboards, alerts, and playbooks that keep AI inside safe, measurable bounds.
Deploy engineers who specialize in retrieval‑augmented generation, structured data pipelines, and integration with your existing tools. They connect CRMs, ticketing, docs, and internal systems so AI can answer real questions and take real actions.
Your team gets context‑aware AI that understands your business, not just generic chatbots typing into thin air.
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We pre‑vet technical skills, communication, and delivery track record so you don’t have to. Each specialist is selected for hands‑on experience with real production systems.
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Every engagement follows Dyntyx patterns for observability, audit trails, and escalation—so your legal, security, and compliance teams can sleep at night.
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Our talent is fluent in modern LLMs, vector stores, orchestration frameworks, and cloud infra—so they fit into your environment instead of forcing a single vendor.[
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Typical clients see their first staffed role in under 30 days and first shipped impact from that role in 4–8 weeks.
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We align every placement to concrete KPIs—hours saved, cycle times, error reduction, or revenue lift—not vague “innovation.”
Flexible models designed for product, ops, and innovation teams. Choose between stable capacity or project‑based flexibility.
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TALENT OFFERING | ENGAGEMENT MODEL | TYPICAL INVESTMENT RANGE* |
|---|---|---|
 Embedded AI Engineer | Hourly or Monthly Retainer | $120–$160/hr or $18k–$20k/mo |
.svg){kind=small} AI Architect & Tech Lead | Fractional or Project‑Based | $160–$250/hr or $25k–$80k/project |
.svg){kind=small} AI Ops & Governance Specialist | Part‑time or Embedded | $120–$180/hr or $20k–$30k/mo |
 AI Data / RAG Engineer | Hourly or SOW | $130–$190/hr or $20k–$60k/project |
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Most organizations don’t fail on AI ideas—they fail on staffing and delivery.
Senior AI practitioners are scarce, and hiring cycles are long.
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Boards and regulators now expect AI to be explainable, observable, and controllable.
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