Your team is doing work an AI agent should be doing. We build the agent.
Compliance checks. Monthly closes. Reporting cycles. Multi-vendor coordination. Most organizations know AI agents are coming but haven't been able to put one to work alongside their existing team. That's where we work.
AI and automation builds
We design and ship AI agents for the workflows eating your team's hours: compliance checks, expense categorization, receipt-to-ledger matching, monthly close assembly. The agents read your source data, apply your rules, and surface what needs human review. Every decision traces back to a named rule and a source quote.
See the service→Tech and AI program management
We have led multi-million dollar technology programs end to end: multi-vendor governance, workstream coordination, sponsor-facing reporting, and delivery assurance. If your AI or digital transformation has to land on a deadline and a budget, we run it.
See the service→Strategic AI advisory
Before you commit to a vendor or a build path, we map your operations and tell you where AI actually earns its place — and where it doesn't. The output is a prioritized roadmap with build, buy, and do-not recommendations, and a gap analysis against NIST AI RMF or ISO 42001.
See the service→We build agents that make your team faster and more effective.
Every agent we build works alongside your existing department. The agent clears the backlog. Your team handles the judgment. Their role becomes more valuable.
Read our commitment→Most companies have heard of AI agents. Very few have put one to work.
An AI agent is not a chatbot. It is not a dashboard. It is an automated system that reads your source data, applies your business rules, and surfaces what needs human review. It runs on a schedule or on demand. It does not make decisions. It flags what needs attention.
You have probably seen AI demos that look impressive. The gap between a demo and a working system that your auditor will accept is engineering discipline: deterministic logic for the work with a right answer, a narrow AI layer for the parts that genuinely need language judgment, and an audit trail on every decision. That gap is where we work.
Here is what an AI agent actually does inside a back office:
Reads
Pulls 1,500 expense receipts from your accounting system, reads each one, extracts amounts, dates, vendor names, and document types. Matches them to your ledger on deterministic keys.
Checks
Categorizes each expense against your chart of accounts. Flags out-of-period items, missing documentation, arithmetic mismatches, and competitive-bid threshold violations.
Surfaces
Generates a sorted flag queue for your team. Every flag carries the rule that fired, the source evidence, and a suggested fix. Your team handles the exceptions. The audit trail builds itself.
The agent does the heavy lifting. Your team stays in the loop, handling the judgment calls and the edge cases the agent surfaces. Their workload shrinks. Their role becomes more valuable. Read how we think about AI and your team.
The math on clearing your backlog.
Your real alternatives are: hire more staff, outsource to a BPO, build an AI agent, or keep doing what you are doing. Here is how they compare.
| Hire in-house | Outsource (BPO) | AI agent build | |
|---|---|---|---|
| Time to productive | 6 to 12 months | 4 to 8 weeks | 8 to 14 weeks |
| Ongoing cost | $150K to $300K/year (2 to 3 FTEs with benefits) |
$80K to $150K/year | One-time build fee + optional annual support |
| Knowledge retention | Walks out the door when someone quits |
Stays with the vendor | Stays with you versioned rule catalog you own |
| Audit trail | Manual documentation | Vendor-dependent | Built into every decision |
| Scales with volume | Linear (more people = more cost) |
Linear (more hours = more cost) |
Near-zero marginal cost |
Recent work
Engagements across government, energy, finance, and technology. Some clients named, others by industry where confidential.
Multi-Funder Non-Profit
AI and Automation Build
We built an AI agent that catches everything a manual reviewer would, plus the documentation gaps the manual process was missing. Every flag carries the rule it triggered and the source quote behind it.
Read the case study →Federal Ministry
$30M+ Tech and AI Program Management
PMO leadership across eight workstreams and five vendor contracts on a multi-year program digitizing 100+ public services for 13M+ residents. One unified picture to the steering committee, every cycle.
Read the case study →Sovereign Investment Fund
$1.2B Portfolio Restructuring
Financial analysis and a structured categorization framework across 40 portfolio companies, supporting an 8% profitability uplift. The framework was built once and is reusable for every future portfolio decision.
Read the case study →Talk to us.
A 30-minute call tells you whether your problem is something we should build for you. If it isn't, we'll tell you which kind of firm would be a better fit, and where to find one.