Chicago Agentic Development
Your competitor’s AI agent looks like a chatbot.
Ours was designed by someone who gives a damn.
We build autonomous AI agents with interfaces people actually want to use. UI-first architecture. Conversion-focused logic. Built for Chicago businesses.
weeks to production
avg. ticket volume reduction
lead volume increase
Built for Chicago’s industries
Logistics
Manufacturing
SaaS
Healthcare
Retail
Your team is doing work an AI agent should be doing.
The hours spent on lead research, ticket triage, onboarding follow-ups, inventory updates, CRM entries — it’s all eatable. By a machine.
Most “AI agents” in production are glorified if/else scripts wearing a chatbot skin. Built by engineers who got the job done. Not by designers who got it right.
-
Agents built without UX — nobody actually uses them -
Integrations bolted on after the fact — they break -
No guardrails, no monitoring — you’re flying blind -
Off-the-shelf agents that look like everyone else’s
if input == “pricing”:
return “Our pricing starts at $X.”
elif input == “demo”:
return “Let me connect you…”
else:
return “Please contact support.”
# Ours looks like this
class Agent:
def __init__(self, intent, memory, tools):
self.context = load_user_history()
self.tools = tools # CRM, ERP, docs…
self.reason() # ← this is the difference
Designed first. Built to last.
We start with the experience. Then we build the intelligence underneath it. Every time.
AI Agent Architecture
We design the experience before we write a line of code. From customer support agents to complex operations orchestrators — built around how people actually think.
- Experience-first wireframes
- Multi-intent handling
- Human escalation paths
- Memory & context management
Multi-Agent Systems
Multiple agents. One coordinated system. Built for workflows that are too complex for a single agent — designed so your team can still understand what’s happening.
- Role-based agent design
- Shared memory & orchestration
- Cross-system integration
- Failure recovery & fallback logic
LLM Integration
We connect your agents to the models that power them — OpenAI, Anthropic, open-source — with the guardrails that keep them honest and the RAG pipelines that make them accurate.
- Model selection & fine-tuning
- RAG-powered knowledge agents
- Guardrails & safety systems
- Performance monitoring
What can an agent actually do for a Chicago business?
Real scenarios. Real outcomes. Not theoretical.
Stop burning your team on the same 40 questions.
Our support agents resolve tier-1 tickets around the clock — and escalate the ones that actually need a human. No generic deflection. Real resolution.
Clients see 40%+ reduction in tier-1 ticket volume within 30 days
Your best SDR researches 15 leads before noon. An agent does it continuously.
Drafts outreach. Updates your CRM. Flags the hot ones. Your team sells. Your agent hunts.
Clients go from 20 → 80+ qualified leads per week
Scheduling. Inventory. Reporting. Running themselves.
Multi-agent systems that handle your operations workflows so your ops team can focus on the work that actually moves the needle.
Fully operational multi-agent systems in 6–12 weeks
Your team is looking for answers in 6 different systems.
We build a RAG-powered agent that knows your docs, your wikis, your SOPs — and answers from them. Without making your team learn a new tool.
Instant answers from your own content. No retraining required.
Sprint by sprint. Demo every two weeks.
We don’t disappear for three months and then show you something unrecognizable. You see progress continuously.
Discovery
We dig into your workflows. Who does what. Where the friction is. What success actually looks like.
Architecture
We design the agent’s experience before we write a line of code. Wireframes. Logic flows. You see it first.
Build
1–2 week sprints. Working software every cycle. Weekly demos. No surprises at the end.
Integration
CRM, ERP, support tools, data pipelines. We build the connections and harden them for production.
Launch & Monitor
Production deployment with guardrails, monitoring, and a feedback loop. We don’t disappear after launch.
Most projects ship a working version in 6–12 weeks.
Chicago businesses. Chicago results.
“We cut our tier-1 ticket volume by 40% in the first month. The agent doesn’t just answer — it learns from every interaction.”
“Our sales team went from 20 qualified leads a week to 80. The agent does the hunting. They do the closing.”
“We shipped a working multi-agent system in 6 weeks. From discovery to production. Not a prototype — production.”
What does this actually cost?
Fixed-fee proposals after a free scoping call. No surprises. No hourly gray zones.
Single Agent
For focused automation — one workflow, one team, one outcome.
- ✓ Discovery + wireframes
- ✓ Single AI agent build
- ✓ 1–2 system integrations
- ✓ Guardrails + monitoring
- ✓ 6–10 week delivery
Multi-Agent Platform
For businesses that need multiple coordinated agents across complex workflows.
- ✓ Full discovery + architecture
- ✓ Multi-agent system design
- ✓ Unlimited integrations
- ✓ RAG knowledge layer
- ✓ 3–6 month delivery
- ✓ Ongoing monitoring & support
Good questions. Real answers.
Yes. Our team spans UX design, interface engineering, and AI systems architecture. We don’t hand off to another shop once the design is done. You work with the same team, start to finish. We’ve shipped production multi-agent systems — not just prototypes.
Most projects ship a working version in 6–12 weeks. Enterprise-grade multi-agent platforms with deep integrations: 3–6 months. We commit milestones in writing and demo every sprint — you’re never waiting months for your first look.
Fixed-fee proposals after a free scoping call. Smaller engagements start in the low five figures; enterprise builds go into six and seven figures. It depends on complexity, integrations, and timeline. We don’t do hourly gray zones — you know the number before we start.
Both. We work with growth-stage startups and mid-market companies — not just Fortune 500s. The same senior team works on every engagement. If you’re moving fast and need an agent that actually works, we’re the right fit.
We’re designers who build AI agents. Most agencies start with the tech stack and figure out the experience later. We start with the experience and build the tech underneath it. That changes everything about how an agent actually performs — and whether your team actually uses it.
Ready to build an agent people actually want to use?
Most AI projects fail not because the model wasn’t good enough — but because nobody designed the experience.
That’s where we’re different.