AI engineering for growing businesses
Build AI agents that work for your business
We design and integrate custom AI agents, automate time-consuming workflows, and build practical LLM-powered applications — backed by 25+ years of software engineering experience.
- Founder-led AI engineering
- Real-world system integration
- Built for business workflows
Supplier invoice, received 9:14 AM
Agent run- Read the email and attached PDF1 invoice, 3 line items
- Extracted the key fieldsInvoice #4471 · $8,240.00 · due Nov 30
- Checked against the purchase orderQuantities match · price differs on 1 line
- Drafted a note for Accounts PayableFlagged the price difference
- Waiting for approvalNothing is paid or sent until a person on your team signs off.
Go beyond AI demos
Generic chatbots are easy to demonstrate. Useful AI systems need to connect securely with your data, tools, and processes.
Big Reel Systems helps turn promising AI ideas into working solutions with clear scope, human oversight, and practical engineering.
What we build
See service detailsCustom AI Agent Development
Agents that retrieve information, use tools, coordinate tasks, and assist employees with real workflows — within defined permissions and review boundaries.
Agentic Workflow Automation
Reduce repetitive work by connecting AI to email, documents, databases, CRMs, and internal business processes — with reliability, visibility, and appropriate approvals.
LLM Integration & AI Applications
Add language-model capabilities to the products and systems you already run: knowledge assistants, document intelligence, retrieval-augmented generation (RAG), and conversational interfaces.
AI systems integration
APIs, CRM and ERP connectors, internal applications, databases, and event-driven workflows.
AI architecture & advisory
Opportunity assessment, framework selection, technical roadmap, security, evaluation, and cost planning.
Ongoing AI engineering
Support, monitoring, iterative improvements, and reliability work after launch.
What this can look like day to day
Illustrative examples, not customer results.
Inbound requests
An agent sorts incoming requests, drafts a response, and sends it to an employee for approval.
Includes a human approval step
Documents
Key fields are pulled from invoices or forms, and anything unusual is routed to a person for review.
Includes a human approval step
Company knowledge
Staff ask questions in plain English and get answers grounded in your own documents, with sources.
Connected systems
Updates flow between email, your CRM, and internal APIs so nobody re-types the same information.
How an engagement works
Step 1
Discover
A free 20-minute conversation about the workflow, your constraints, and the business objective.
Step 2
Scope
We identify the smallest valuable pilot and agree on security, integrations, acceptance criteria, timeline, and fees.
Step 3
Build
A focused solution is implemented with testing, human oversight, and documentation your team can use.
Step 4
Improve
We measure how it performs, then extend or support the system when the results justify it.
Senior engineering experience. Hands-on delivery.
Big Reel Systems is led by its Founder & Principal Software Architect, who brings more than 25 years of experience developing software and integrating complex systems.
That engineering foundation helps bridge the gap between exciting AI prototypes and dependable business applications.
Common questions
What kinds of business processes can AI agents automate?
Good candidates are repetitive, text-heavy tasks with clear rules for what a good outcome looks like: sorting and answering requests, pulling information out of documents, looking things up across several systems, and preparing drafts for a person to review.
Can you integrate AI into our existing software?
Yes. Most projects connect to systems you already use — email, CRMs, databases, internal applications, and APIs — rather than replacing them.
Do we need to know which AI model or framework to use?
No. Choosing the model and tooling is part of the work, based on your requirements for quality, privacy, and running cost.
How do you manage data privacy, permissions, and human approvals?
Each agent gets only the access its workflow needs. Actions with real consequences, such as sending messages, making payments, or changing production data, go through a person for approval. Data handling is agreed in writing during scoping.
Can we start with a small pilot?
Yes, and that is the recommended approach. A focused pilot on one workflow shows whether the approach works before you commit to more.
Do you offer ongoing engineering support?
Yes. After launch, support, monitoring, and improvements are available on a retainer.
Have a process you want to automate?
Let's identify a practical AI opportunity and discuss the right first step.