Your department has been told to “adopt AI.” Now what?
Your team tried ChatGPT. Maybe someone set up a Copilot workspace. It's useful for answering questions about company docs — but it can't pull data from your ERP, route an invoice through your approval chain, or flag that a vendor contract deviates from your standard terms.
The gap between “AI that answers questions” and “AI that does work” is an engineering problem. It starts with understanding your processes and your data.
You're probably also building the business case internally. Multiple stakeholders — IT, compliance, procurement, your leadership — all need to be aligned before anything moves forward. We've been through that process with other teams and can help you frame it.
What we hear from department leaders
Q: "We don't have AI engineers on the team."
You don't need to hire them. We embed with your team for the build, then hand off a working system with training and documentation.
Q: "We tried off-the-shelf tools but hit a wall."
That wall is usually system access. Off-the-shelf tools can read your docs but can't take action in your Salesforce, ERP, or accounting system. Custom agents can.
Q: How do we know the agent won't make mistakes?
Every agent has defined guardrails — what it can decide alone, what requires human approval, and what it should never do. You set those boundaries.
Q: "Our data is sensitive. We can't just pipe it into ChatGPT."
Custom agents run in your environment with your security controls. ISO 27001 certified. Your data stays yours.
What an AI agent actually is
In simple terms an AI agent is software that uses a large language model to understand tasks, connects to your business systems to get information and take action, and follows rules you define.
How an AI agent works
Your Team
Chat interface
Slack / Teams
Email trigger
Scheduled run
Events fire
LLM (The Brain)
Claude, GPT-4, Llama - picks the right one for your use case
Prompt & Context
Your rules, your playbook, your terminology
Guardrails
What it can do, what it can't, when it asks a human
Memory & Knowledge
Your reference data, past decisions, and the context it carries across runs
Your Systems
Docusign / CLM
Salesforce / CRM
SAP / ERP / Xero
SharePoint / Google Drive
The agent reads from and writes to your systems through secure API connections - it doesn't just answer questions, it takes action.
The Brain (LLM)
A language model (Claude, GPT-4, or open-source) that understands natural language, reasons about tasks, and decides what to do next. We pick the right model for your cost, speed, and accuracy requirements.
Tools & Connections
API integrations that let the agent read from and write to your systems — your CRM, ERP, document management, accounting software. This is where off-the-shelf tools fall short and custom engineering matters.
Guardrails & Rules
Defined boundaries: what the agent can decide alone, what needs human approval, what it should never do. Your compliance requirements, your approval thresholds and your escalation rules.
Monitoring & Logging
Every action the agent takes is logged. What it read, what it decided, what it did. Full audit trail. You see what it handled, what it escalated, and where it needs tuning.
The Brain (LLM)
A language model (Claude, GPT-4, or open-source) that understands natural language, reasons about tasks, and decides what to do next. We pick the right model for your cost, speed, and accuracy requirements.
Tools & Connections
API integrations that let the agent read from and write to your systems — your CRM, ERP, document management, accounting software. This is where off-the-shelf tools fall short and custom engineering matters.
Guardrails & Rules
Defined boundaries: what the agent can decide alone, what needs human approval, what it should never do. Your compliance requirements, your approval thresholds and your escalation rules.
Monitoring & Logging
Every action the agent takes is logged. What it read, what it decided, what it did. Full audit trail. You see what it handled, what it escalated, and where it needs tuning.
Agents we build for enterprise teams
Each agent is scoped to a specific job within a specific department. Not a general-purpose chatbot – a specialist that does one thing well.
Contract Review Agent
Your legal team reviews hundreds of incoming contracts against your standard playbook. Every contract takes 30-60 minutes of manual comparison.
WHAT THE AGENT DOES
- Reads incoming contracts and compares against your clause library and playbook
- Flags deviations from standard terms (indemnity caps, liability limits, IP clauses)
- Drafts redline suggestions in your preferred format
- Escalates high-risk deviations to a senior reviewer with a summary
- Logs every review decision for audit compliance
CONNECTED SYSTEMS
TARGET OUTCOME
Cut first-pass review time from 45 minutes to under 5 minutes per contract.
Obligation Tracking Agent
Signed contracts contain deadlines, renewal dates, and compliance obligations buried across hundreds of documents. Teams miss them.
WHAT THE AGENT DOES
- Extracts all obligations, deadlines, and renewal dates from signed agreements
- Creates a live obligation register linked to source documents
- Sends proactive alerts 90/60/30 days before deadlines
- Generates compliance status reports for leadership
- Flags conflicting obligations across related agreements
CONNECTED SYSTEMS
TARGET OUTCOME
Zero missed renewals. Full obligation visibility across the portfolio.
Why not just use Dust or ChatGPT Enterprise?
Off-the-shelf AI platforms are useful. We use them too. But they have a ceiling. Here's where it is.
OFF-THE-SHELF AI TOOLS
Dust, ChatGPT Enterprise, Copilot Studio
Good for general Q&A on company knowledge. Breaks down when you need more.
CUSTOM AI AGENT BY FLUIDLABS
Purpose-built for your department
Does everything the platforms do, plus the things they can't.
If your department just needs Q&A on company docs, use Dust. It's $30/user/month and it's good. If you need AI that takes action in your systems, follows your compliance rules, and handles real workflows – that's a custom build. That's us.
How We Build Your Agent
Every engagement follows the same structure. Clear phases, defined deliverables, no surprises. Typical timeline: 6-10 weeks from discovery to production.
Discovery
- We sit with your team. Watch the workflow. Ask the questions that matter.
- Map every system the agent will need to touch - and who controls access.
- Define what "success" looks like in numbers: time saved, errors caught, volume handled.
- Identify guardrails: what the agent can decide alone vs. what needs a human.
Architecture & Design
- Choose the right LLM for your requirements (cost, speed, accuracy, data residency).
- Design the tool integrations - which APIs, what data flows, what permissions.
- Build the prompt architecture: your rules, your terminology, your edge cases.
- Design the human-in-the-loop checkpoints and escalation paths.
- Deliverable: Technical architecture, security model, and integration plan.
Build & Test
- Develop the agent. Connect to your systems in a sandbox environment.
- Test with real data samples. Iterate with your team weekly.
- Tune prompts and guardrails based on edge cases your team surfaces.
- Load test for your expected volume. Validate security controls.
- Deliverable: Working agent in staging, ready for team review.
Deploy & Train
- Deploy to your production environment.
- Train your team: what the agent does, how to use it, when to escalate.
- Run in supervised mode - agent works, team validates, we tune.
- Complete documentation: architecture, runbooks, troubleshooting guides.
- Deliverable: Production agent, trained team, full documentation.
Monitor & Maintain
- Agents aren't fire-and-forget. We monitor performance continuously.
- Monthly reporting: tasks handled, escalations, accuracy, edge cases.
- Prompt tuning as your processes and rules evolve.
- System connection updates when your platforms change.
- Deliverable: Monthly performance report and continuous improvement.
BUILD TIMELINE
WHAT YOU OWN AT THE END
- Working production agent
- Full source code and documentation
- Architecture and runbook
- Team training completed
- Monitoring dashboard access
The Work That Comes First
42% of companies abandoned most AI initiatives in 2025. The top reason? They started with the technology. We start with your operations.
1. Map the Workflows That Matter
We start with your existing process documentation - or build it if it doesn't exist. We map the specific workflows where an agent will operate: every branching decision, every handoff, every system touchpoint. The workflows where automation has the highest impact and the clearest path to production.
2. Identify Where AI Fits
Not everything needs an agent. Some processes need simple automation. Some should stay manual. We identify exactly which parts of each workflow benefit from AI reasoning - and which are better served by a rule or a script.
3. Assess Data & System Readiness
Data quality is the #1 reason AI projects fail - 85% of failures trace back to it. We assess whether your data is clean and structured enough for an agent to use reliably. We check that your systems have the API connectivity an agent needs. If the connectivity doesn't exist, we build it. If your data isn't ready, we'll tell you - and help you fix it first.
4. Design for Adoption
48% of employees would use AI more with proper training. 45% would use it more if it fit into their daily workflow. We train your team, embed the agent into existing workflows, and run in supervised mode until the team trusts the output.
1. Map the Workflows That Matter
We start with your existing process documentation - or build it if it doesn't exist. We map the specific workflows where an agent will operate: every branching decision, every handoff, every system touchpoint. The workflows where automation has the highest impact and the clearest path to production.
2. Identify Where AI Fits
Not everything needs an agent. Some processes need simple automation. Some should stay manual. We identify exactly which parts of each workflow benefit from AI reasoning - and which are better served by a rule or a script.
3. Assess Data & System Readiness
Data quality is the #1 reason AI projects fail - 85% of failures trace back to it. We assess whether your data is clean and structured enough for an agent to use reliably. We check that your systems have the API connectivity an agent needs. If the connectivity doesn't exist, we build it. If your data isn't ready, we'll tell you - and help you fix it first.
4. Design for Adoption
48% of employees would use AI more with proper training. 45% would use it more if it fit into their daily workflow. We train your team, embed the agent into existing workflows, and run in supervised mode until the team trusts the output.
Pricing
Every agent is scoped individually based on workflow complexity, number of system integrations, and compliance requirements.
FIRST AGENT — TYPICALLY
$30,000–$60,000
Fixed before work starts
AFTER LAUNCH
Most agents cost $1-5K/month to operate (LLM usage, monitoring, infrastructure). Annual maintenance runs 15-30% of the initial build cost. We offer ongoing support, or your team can manage independently.
30-minute scoping call. No commitment. We'll tell you honestly if a custom agent is the right fit — or if an off-the-shelf tool would serve you better.
Not ready to commit to a build? Start with a $12,000 AI Opportunity Assessment — a two-week diagnostic that maps one workflow, puts a real dollar figure on it, and is credited 100% to your build if you go ahead.
What affects the price?
Number of system integrations - an agent that connects to one system costs less than one that orchestrates across four.
Workflow complexity - a straightforward approval flow vs. multi-branch conditional logic with exception handling.
Compliance requirements - regulated industries need more guardrails, testing, and documentation.
Data volume - processing 100 invoices/month vs. 10,000 changes infrastructure requirements.
BUILD TIMELINE
Fluidlabs (Fixed scope, 6-10 weeks, you own everything)
$30K–$60KConsulting firm (3-7x more for equivalent scope)
$100K - $200KIn-house team (1-4 AI engineers required)
$125K - $500K/yrAlready have agents? Need connectivity?
If you're using Dust, ChatGPT Enterprise, or Copilot and just need your agents connected to your internal systems, get in touch. We build the bridges without rebuilding your agents.
Frequently Asked Questions
Further Reading
Ready to Scope Your First Agent?
Schedule a 30-minute strategy session. We'll identify the highest-value vertical solution for your organization, walk through the architecture, and map out a build plan — no commitment required.
Scope Your First Agent →or email us at [email protected]