AI that takes action not just answers questions

Custom AI agents that plan, decide, and execute multi-step workflows across your tools autonomously, reliably, and with humans in the loop where it matters.

Request a quote See agent types

−80%

Manual work cut

24/7

Autonomous run

4–8

Week build

You probably need AI agents if...

Your team does repetitive multi-step workflows across tools every day

You want AI to actually do things research, write, send, schedule

You've tried Zapier or n8n and hit limits where the work needs judgment

You need a 24/7 digital worker that scales without hiring

Agents are powerful and require careful guardrails

For deterministic, single-step tasks, plain automation is cheaper and safer. Agents make sense when the work needs reasoning, decisions, or adapts to context.

Six agent patterns one framework

Each agent solves a different shape of problem. Most production systems use 2–3 patterns together.

Research agents

Browse web, read docs, gather data, write reports. For market intel, lead enrichment, due diligence.

Sales & outreach

Identify leads, personalize emails, follow up, log to CRM, book meetings.

Support agents

Triage tickets, look up data, draft responses, escalate when needed.

Ops agents

Process invoices, onboard customers, sync data between tools, run reports.

Coding agents

Write code, run tests, open PRs, review changes. Internal dev acceleration.

Multi-agent systems

Multiple agents coordinating planner, researcher, writer, reviewer for complex tasks.

Anything with an API most of what your team already uses

Agents become useful when they can act in real tools, not just chat. We wire them into your existing stack.

Communication

Gmail · Outlook · Slack · Discord · WhatsApp · SMS

Calendar & meetings

Google Cal · Outlook · Calendly · Zoom · Meet

CRM & sales

HubSpot · Salesforce · Pipedrive · Apollo · Clay

Docs & storage

Notion · Google Drive · Dropbox · Airtable

Data & analytics

Postgres · BigQuery · Snowflake · Mixpanel

Web & search

Web browsing · SerpAPI · Tavily · Exa search

Support & ticketing

Zendesk · Intercom · Freshdesk · Linear · Jira

Custom APIs

Your internal systems · Webhooks · OpenAPI · MCP

Every agent build includes

Production-grade agents with guardrails, evals, and observability not a demo that breaks in week 2.

Workflow mapping

Define decisions, steps, tools, edge cases

Reasoning engine

ReAct, plan-and-execute, or graph-based

Tool integrations

Connections to your existing stack

Memory & context

Short-term + long-term memory layers

Human-in-the-loop

Approval gates for high-stakes actions

Guardrails & safety

Rate limits, scopes, action filters

Eval & monitoring

Track success rate, cost, latency in production

Audit trail

Every action logged for review & compliance

Control dashboard

Start, stop, configure, and review your agent

Power without the chaos

Autonomous agents only work in production with layered guardrails. Every system we build has all four.

Scoped permissions

Agents can only access tools and data you explicitly grant. No surprises.

Approval gates

High-stakes actions (sending external email, payments, deletions) require human approval.

Rate limits & budgets

Hard caps on actions per hour and API spend per day no runaway agents.

Full observability

Every decision, tool call, and outcome logged with full traces. You can audit anything.

Framework we build with

Claude Agent SDKOpenAI Agents SDKLangGraphLangChainMCP (Model Context Protocol)Vercel AI SDKInngestTemporalLangSmithPineconeSupabaseModal

From workflow to live agent in 5 phases

Agents need extra rigor we prove the workflow works before turning autonomy up.

Week 1

Discovery

Map workflow, tools, success metrics

Week 2

Prototype

Working agent on 1–2 tools, dry run

Week 3–5

Build

Full tools, memory, guardrails

Week 6

Eval & supervise

Shadow mode with human approval

Week 7–8

Deploy

Live agent + monitoring dashboard

Find the engagement that fits

Every agent project is quoted based on complexity, tools, and autonomy required.

Engagement 01

Agent Sprint

2-week proof of concept

Single-purpose agent
1–2 tool integrations
Working prototype
Demo + ROI analysis
Recommendations for v2

Request a quote

Most common

Engagement 02

Agent Build

6–8 week production build

Full production agent
5–10 tool integrations
Memory + guardrails
Human-in-the-loop UI
Eval & monitoring
60-day support

Request a quote

Engagement 03

Agent Platform

3+ month partnership

Multi-agent system
Unlimited integrations
Customer-facing agents
Self-hosted (optional)
Continuous improvement
Dedicated AI engineer

Request a quote

Every AI project is different so is every quote

After a 30-minute scoping call, we send a detailed proposal within 3 business days including workflow map, autonomy boundaries, and a fixed all-in price. Model API costs (Claude, GPT, etc.) are estimated and paid separatelyagents typically run $100–$2,000/month depending on volume.

Scoping call

Free 30-min on workflow, tools, autonomy.

Custom proposal

Scope, timeline, fixed price within 3 days.

Kickoff

Discovery sprint within 1–2 weeks.

Things people ask before starting

A chatbot answers questions in a conversation. An agent plans multi-step work, uses your tools (email, CRM, calendar, APIs), and completes tasks end-to-end. Many production systems combine both users chat, the agent acts.

Zapier and Make excel at deterministic, single-path automation. Agents make sense when steps need judgment, branching, unstructured input, or adapting to context like triaging support tickets, researching leads, or deciding which follow-up to send.

We design for safe failure: scoped permissions, approval gates on high-stakes actions, rate limits, full audit trails, and shadow mode before full autonomy. You can pause, roll back, or require human sign-off on anything sensitive.

Only what you explicitly grant. We scope tool access per workflow, support VPC and self-hosted deployment for regulated data, and never train on your customer data without contract clarity. PII handling and retention policies are defined in scoping.

Start with human-in-the-loop or shadow mode, then increase autonomy as accuracy proves out. We map autonomy boundaries in week one which actions run automatically vs. need approval so you control risk while still cutting manual work.

Yes. Production agents include eval suites, feedback loops, and prompt or policy updates from real runs. Platform engagements add continuous improvement we monitor success rate, cost, and edge cases and refine the agent on a regular cadence.

AI automation

For deterministic, no-judgment workflows. Cheaper and simpler than agents.

RAG systems

Give your agent grounded knowledge from your docs & data.

AI chatbots

Conversational front-end for your agents users chat, agents act.

Got a workflowworth automating?

Book a free 30-minute call. We'll map your workflows, recommend the right architecture, and send a proposal within 3 days.

Request a quote

AI that takes action not just answers questions

You probably need AI agents if...

Six agent patterns one framework

Anything with an API most of what your team already uses

Every agent build includes

Power without the chaos

Framework we build with

From workflow to live agent in 5 phases

Find the engagement that fits

Every AI project is different so is every quote

Things people ask before starting

Related services

Got a workflowworth automating?

Six agent patterns one framework

Anything with an API most of what your team already uses

Every agent build includes

Power without the chaos

Framework we build with

From workflow to live agent in 5 phases

Find the engagement that fits

Every AI project is different so is every quote

Things people ask before starting

Related services