AI agents that do the work,not just the talking.
Custom agents that plan, decide and act across your tools, with a human approving what matters.
"Hi Sarah, thanks for reaching out. Would Thursday 11:00 or Friday 15:00 work for a quick call?"
What is an AI agent?
Software you give a goal, not a script. It reads your tools, decides what to do next, takes action and checks the result.
Unlike a chatbot, it finishes the task. Unlike basic automation, it handles situations nobody planned for, and it knows when to stop and ask a person.
Watch one work ›Goal
What you want doneTools
Your CRM, inbox, ERPMemory
Context from each stepGuardrails
Rules and human approval
Watch an agent think it through.
Every AI agent runs the same loop until the job is done. On the right, a real-world example: a customer asks to move a delivery.
- 01
Perceive
Reads the request and the data around it: emails, CRM records, orders, documents.
- 02
Plan
Breaks the goal into steps and decides which tools it needs.
- 03
Act
Uses your tools through secure connections: updates records, sends messages, books slots.
- 04
Check
Verifies the result, logs every step, and asks a person if something looks off.
One agent per job. Trained on your business.
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Blu · Sales agent
Never miss a warm lead again.
Qualifies every inbound lead within minutes, writes a personal follow-up and books the call, so your sales team only talks to people ready to buy.
- Scores leads on budget and fit
- Drafts personal follow-ups
- Books calls into calendars
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Pip · Support agent
Answers in seconds, any hour.
Resolves order, booking and account questions on your website, email and WhatsApp, and hands tricky or unhappy customers to a person with full context.
- Answers from your help docs
- Updates orders and bookings
- Escalates with a summary
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Ozzy · Operations agent
Keeps the back office moving.
Processes invoices and purchase orders, keeps every system in sync and chases missing documents, so operations never wait on manual data entry.
- Reads invoices and POs
- Syncs ERP, CRM and sheets
- Chases missing paperwork
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Iris · Insights agent
Answers "how are we doing?"
Pulls numbers from every tool, writes a plain-English weekly report and flags unusual changes early, so leaders decide with facts, not guesses.
- Weekly performance reports
- Spots unusual changes
- Answers data questions
You decide how much it does on its own.
Most clients start at "Draft & approve" and give the agent more freedom as trust grows. Every level comes with the same safeguards.
Human approval
Choose exactly which actions always need a person.
Full audit trail
Every decision and tool call is logged and searchable.
Least-privilege access
Agents only see the systems and data you approve.
Tested before launch
We evaluate agents on real cases before they go live.
From first call to a working agent.
A focused first agent is usually live in about six weeks, tested on your real cases before it ever talks to a customer.
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Week 1
Discovery call
We learn your goals, map the task the agent will own and agree what "done well" looks like.
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Week 1–2
Agent design
We define the agent's tools, rules, tone and the actions that always need a person.
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Weeks 2–5
Build and connect
We build the agent and connect it securely to your CRM, inbox and other systems.
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Week 5–6
Evaluate on real cases
The agent is tested on hundreds of real examples until it performs the way your best person would.
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Ongoing
Pilot and scale
We launch with approvals on, monitor quality and cost, and widen its freedom as results prove out.
The frameworks and models behind our agents.
We build agents on open, well-supported tools, so you are never locked into one vendor or model.
Agent frameworks
The code foundations that give agents tools, memory, handoffs and guardrails.
LangChainChains, tools and retrieval for LLM apps
CrewAITeams of agents with defined roles
LlamaIndexConnect agents to your documents and data
OpenAI Agents SDKTool use, handoffs and guardrails
AI models
The reasoning engines, selected per agent for accuracy, speed and cost.
Anthropic ClaudeCareful reasoning on long documents
Google GeminiMultimodal models across Google Cloud
Workflow automation
Platforms that connect agents to triggers, approvals and the apps your team uses.
n8nSelf-hosted workflows with custom code steps
MakeVisual scenarios for multi-app automations
ZapierQuick no-code links between 6,000+ apps
Voice & telephony
For agents that pick up the phone, make calls or speak with customers.
TwilioPhone numbers, calls, SMS and WhatsApp APIs
VapiReal-time voice agents over phone and web
Retell AILow-latency voice calls with natural turn-taking
ElevenLabsLifelike voices in 30+ languages
Memory & vector data
Where agents store and search knowledge so answers stay grounded in your data.
PineconeManaged vector search for agent memory
WeaviateOpen-source vector database
SupabasePostgres, auth and vector search in one
PostgreSQLReliable relational data storage
Logos are trademarks of their respective owners, shown to indicate the tools we build with.
Your agent works inside your stack.
Agents don't need a new platform. They connect to the tools your team already uses, read what they need and act there, so work shows up exactly where people expect it.
Using an ERP, database or in-house system? If it has an API, export or inbox, we can usually connect it, with access limited to what you approve.
Ask about your tools ›Logos are trademarks of their respective owners, shown to indicate compatibility.
Three ways to engage. Pick what fits.
We offer flexible models including fixed-cost projects, dedicated development teams, and time-and-material engagements, depending on what fits your project best.
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Recommended for you
Fixed-cost project
You know what you need built.
Fixed price
agreed up front
- Best for
- MVPs and clearly scoped projects
- Timeline
- A simple MVP can take 4-8 weeks
- You get
- Written scope, milestones, handover
-
Recommended for you
Dedicated team
You want engineers who feel in-house.
Monthly
per team member
- Best for
- Ongoing product development
- Timeline
- Long-term, scale up or down
- You get
- Your own developers, designers and QA
-
Recommended for you
Time & material
Your scope will evolve as you learn.
Hourly
pay only for hours worked
- Best for
- R&D, AI pilots, changing requirements
- Timeline
- Flexible, sprint by sprint
- You get
- Weekly reports and full transparency
AI agent development questions, answered.
What is AI agent development?
- AI agent development is designing and building software agents that pursue a goal on their own: reading data from your tools, deciding the next step, taking action and checking the result, with a human approving important actions.
How is an AI agent different from a chatbot?
- A chatbot answers questions in a conversation. An AI agent completes tasks across your systems, like qualifying a lead, updating your CRM and booking a call, and only involves a person when needed.
How long does it take to build an AI agent?
- A focused first agent for one workflow typically takes a few weeks, including testing on real cases. Larger multi-agent systems take longer; we share a detailed timeline after the first call.
Is my data safe with an AI agent?
- Yes. Agents only access the systems and data you approve, actions are logged, and we're happy to sign an NDA before any discussion begins.
Which tools can your AI agents connect to?
- Common CRMs, email, WhatsApp, Slack, spreadsheets, e-commerce and payment platforms, plus your own databases and APIs.