// 01 · Practice Area

AI agents that
actually ship.

Single-purpose and multi-agent systems built on Claude, GPT, and open-source models — deployed into the tools your team already uses. Customer support, internal copilots, sales co-pilots, voice agents, and orchestrated multi-agent workflows. Production-grade from day one.

4-12
Week timelines
$7.5K
Starting investment
30-90
Days support
// Live System Architecture
A Studios-built agent.
// Input User intent
// Orchestrator Claude Sonnet 4.6
// Tools CRM · Docs · API
// Eval Guard + Log
// Output Action / Response
// Latency < 2s ● PROD

Four agent archetypes.
One delivery standard.

Every Studios-built agent ships with the same rigor — defined evals, guardrails, observability, and a runbook your team can operate. No black boxes.

// 01 — Customer-Facing

Customer support agents

AI-first support deployed in chat, email, voice, or in-app — handles tier-1 volume, escalates with full context to humans, and improves from every transcript with proper eval loops.

  • Multi-channel deployment (chat, email, voice)
  • Human-handoff with full conversation context
  • Knowledge base integration (works with RAG)
  • Sentiment routing and priority detection
// 02 — Internal Copilots

Internal copilots & assistants

Domain-specific assistants embedded where your team already works — Slack, email, your internal tools — handling research, drafting, summarization, and routine analysis with your data and tone.

  • Slack, Teams, and email-native deployment
  • Role-aware: sales, ops, legal, finance, HR variants
  • Trained on your playbooks, voice, and policies
  • Built-in access controls and audit logs
// 03 — Multi-Agent

Multi-agent workflows

Multiple specialized agents working in coordination — a researcher, a writer, a reviewer, an executor — orchestrated to complete complex tasks that no single agent can.

  • Agent-to-agent protocols and handoffs
  • Specialized roles with bounded scope
  • Human-in-the-loop checkpoints
  • Failure recovery and retry logic
// 04 — Voice & Realtime

Voice agents

Production voice agents for inbound or outbound calls — natural conversational latency, CRM integration, call routing, and real-time transcription. Built on the latest realtime AI voice APIs.

  • Inbound IVR replacement or augmentation
  • Outbound qualification and appointment setting
  • Real-time transcription and call summaries
  • CRM auto-logging post-call

Real agents. Real production.

A selection of agent patterns we've built and the typical engagement that delivered them. Names redacted where confidentiality applies; portfolio brands shown where public.

// CONSUMER TRAVEL

Compass AI — Travel Planning Agent

Consumer-facing AI travel planner built on Claude API for Budget Travel Babes. Freemium and paid tiers with usage-aware rate limiting and a member personalization layer that learns trip preferences.

Built in Studios Growth · 10 weeks · Launched to 24K+ waitlist
// FINANCIAL INTELLIGENCE

Boss IQ — Multi-Agent Trading Intelligence

Multi-agent analyst, validator, and compliance-language layers for Boss Traders AI. Explainable analysis, validated signals, and a shared infrastructure that scales across three sibling brands.

Built in Studios Enterprise · 20 weeks · 3 brands deployed
// NONPROFIT OPS

Mavenly — Grant Management Agent System

End-to-end AI grant platform — discovery, drafting, review, submission tracking. Multi-agent workflow purpose-built for mission-driven organizations without dedicated grants teams.

Built in Studios Enterprise · 16 modules · Production deployment
// EDTECH

María — Spanish Tutor Agent

Conversational AI Spanish tutor with persistent learner memory, adaptive difficulty, and a 26-week curriculum graph. Embedded in Habla app for Deep Learn Institute.

Built in Studios Growth · Persona + curriculum design
// SALES OPS

Sales Copilot Pattern

Internal copilot trained on your ICP, CRM history, and sales playbook. Drafts outreach, summarizes calls, surfaces next-best-actions — embedded in Slack and your CRM.

Productized · $18,000 · 5 weeks to production
// VOICE

Inbound Voice Agent Pattern

Production voice agent for inbound or outbound calls — built on realtime AI voice APIs, CRM-integrated, ready for live traffic. Replaces or augments traditional IVR.

Productized · $20,000 · 5 weeks

Four phases.
Working software every Friday.

No black-box delivery. You see weekly demos, you approve evals before they ship, you get a runbook your team can operate at handoff.

01

Discovery & Eval Design

Stakeholder interviews, success criteria definition, and most importantly — the evaluation rubric. We agree on how we'll measure "done" before we write any code.

Week 1
02

Architecture & Prompts

Model selection, agent boundaries, tool definitions, guardrails, and prompt design. You see the blueprint and the first prompt set before we build.

Weeks 1–2
03

Build & Iterate

Engineering sprints with Friday demos. Each demo is a working agent against the eval set. Changes happen in the build, not after delivery.

Weeks 2–10
04

Launch & Train

Production deployment, observability hookup, team enablement, runbook handoff. We don't disappear at launch — your team is trained on operating what we built.

Final 2 weeks

From a single agent
to a full system.

Most clients start with our productized Claude Agent Builder, then expand into multi-agent workflows as the impact compounds. Fixed scope, fixed price for productized; custom scoping for Growth and Enterprise tiers.

Claude Agent Builder
Productized · Fixed Price
$7,500
3 WEEKS · IDEAL FIRST BUILD
  • Single custom AI agent on Claude API
  • Deployed to your environment
  • One business-system integration
  • 14-day post-launch support
  • Training video for your team
  • Eval rubric and runbook included
Start with this
Studios Enterprise
Enterprise · 500+ employees
$150K+
16–26 WEEKS
  • Full multi-agent system buildout
  • Custom fine-tuning when warranted
  • Multi-system architecture
  • AI governance framework
  • Embedded team training
  • Executive reporting cadence
Request a proposal

Stack-agnostic where it matters.
Opinionated where it counts.

We deploy on what your team can operate, not what gets us a kickback. Our default agent stack — adjusted per engagement.

// Models
  • Anthropic Claude
  • OpenAI GPT
  • Google Gemini
  • Open-source (Llama, Mistral)
// Orchestration
  • LangChain & LangGraph
  • Inngest · Trigger.dev
  • n8n · Zapier
  • Custom Python / Node
// Deployment
  • Vercel · AWS · GCP
  • Cloudflare Workers
  • Supabase · PlanetScale
  • Docker + your infra
// Observability
  • LangSmith · Langfuse
  • Datadog · Sentry
  • Custom eval pipelines
  • Cost & latency dashboards

Things buyers ask.

Real questions from real prospects. If yours isn't here, ask us on the discovery call.

Off-the-shelf tools optimize for the average customer. Custom agents optimize for your customer. We build agents that know your product, your tone, your edge cases, your integrations, and your data — none of which a generic platform can replicate. We also own the eval loop, which is the actual difference between a chatbot that works for 60% of cases and one that ships at 95%+.
Depends on your use case, latency budget, data sensitivity, and cost ceiling. For most enterprise agent workloads we default to Claude (Anthropic's enterprise terms and tool-use quality lead the field). For high-volume consumer agents, GPT can win on cost. For regulated or on-prem use cases, fine-tuned open-source (Llama, Mistral) is sometimes the right answer. We recommend during discovery, not before.
You own the custom code, custom prompts, and project-specific configurations developed for you — assigned on full payment. We retain ownership of our methodologies, prompt libraries, and evaluation frameworks (our "Background IP"), which are licensed to you perpetually as embodied in your deliverables. Full details in our Terms of Service.
Foundation model deprecation is a real risk and we plan for it. We architect every agent to make model swaps cheap — the orchestration, prompts, and evals stay; the model behind them changes with a one-line config flip. When a model deprecates, we recommend migration alternatives and quote any rework as a change order. Retainer clients get migration handled as part of monthly hours.
Three layers: (1) retrieval grounding — we pair agents with your verified data sources so they answer from your facts, not the model's training data; (2) eval rubrics that score every change against an accuracy benchmark we agree on in Week 1; (3) confidence thresholds — agents are configured to escalate to humans below a defined confidence floor instead of guessing. Eliminating hallucinations entirely is not the right goal. Catching them is.
No. We select model providers whose enterprise terms guarantee no training on API inputs (Anthropic, OpenAI Enterprise, others). Studios does not train its own foundation models, and we do not use your data to improve services for other clients unless explicitly permitted in your engagement agreement. Details in our Privacy Policy §5–6.
For a Claude Agent Builder (productized): discovery call in week 0, SOW signed and 50% deposit in week 1, three weeks of build, in production by end of week 4 — so about 4–5 weeks calendar time from first call. For Studios Growth: typically 10–14 weeks calendar. Studios Enterprise: 4–6 months. We can move faster when timelines demand it; we'd rather move at the right speed for the right outcome.
Yes. Every engagement includes a support window (14–90 days depending on tier). Beyond that, our Retainer offering ($5K–$25K/month, 12-month minimum) covers ongoing prompt optimization, new workflow builds, performance monitoring, and dedicated engineer hours. About 40% of Growth and Enterprise clients convert to retainer post-launch.

Let's build the agent
your team actually needs.

Tell us what you're trying to solve. We'll respond within 48 hours with a recommended path — productized service, custom engagement, or honest advice to wait.