Advisory · Applied AI
Task-specific AI agents, built on numbers you can defend.
Scoped, architected, engineered and handed over — for enterprises in food, beverage, restaurants, CPG and fintech. You own the result. It runs in your stack, under your name, on your terms.
This is client work. It is not a venture, and it is not a division — it is an advisory engagement delivered through Bailiwick Venture Studio and BailiwickVibe.
The problem with most agent projects
An agent is only as defensible as the data underneath it.
Almost every agent being built today sits directly on operational data that was never reconciled, never governed, and never certified. The agent does not know that. It answers anyway, fluently and with total confidence.
An agent that confidently reports the wrong food cost is worse than no agent, because a human would have hesitated. Ours are built the other way around: the trust layer first, the agent second. That is not a feature comparison — it is a different category of engagement, and it is the reason to hire us rather than an agency that will happily point a model at your POS.
The layer we use is the Metrics Governance Engine, built by FohBoh.ai. It is a required part of every architecture we deliver. We do not make exceptions to that.
Non-negotiable
We do not build agents without a trust layer.
This is a condition of engagement, not a preference. Every architecture we deliver includes the Metrics Governance Engine — MGE — the deterministic certification layer built by FohBoh.ai. Data is sealed on arrival, normalized, reconciled across authoritative sources, scored against trust gates, and issued as a certified operational fact before any agent is permitted to reason over it.
If the inputs cannot be certified, the agent does not get to answer. A blocked answer is a feature. It is the difference between a system that says “I cannot verify this” and one that invents a confident number your team then acts on.
Deterministic, not probabilistic
MGE contains no AI. It is rules, reconciliation and cryptographic sealing — which is precisely why it can be the thing an agent is checked against.
Evidence attached to every answer
Lineage back to source transactions, so an agent’s output can be defended to a controller, an auditor, a franchisee or a lender.
Certification before consumption
The layer sits between your operational systems and the agent, so neither the source system nor the model can influence what counts as true.
MGE is licensed from FohBoh.ai. A license fee is payable to FohBoh.ai and is separate from Bailiwick’s engagement fees.
You will see both numbers before you sign anything. Disclosure: Bailiwick Ventures founded FohBoh.ai and holds an ownership interest in it, so a portion of what you pay for the trust layer returns to us. We would rather tell you that at the start than have you discover it later. If you would prefer to evaluate the certification layer independently, we will support that — but we will not build the agents without one.
Where we are genuinely expert
Five industries, not fifty.
We do not take work in categories we do not know. Domain fluency is the difference between an agent that produces plausible output and one an operator will actually act on — because knowing that theoretical and actual usage diverge for real operational reasons is not something a model infers from a schema.
Four decades on the floor and above it
Multi-unit and franchise operations, POS fragmentation, above-store reporting, labor and scheduling, delivery marketplaces, franchisee compliance, and the reporting a franchisor owes its system.
Cost, supply, and waste
Recipe and menu costing, theoretical versus actual variance, inventory and counts, purchasing and distributor invoices, shrink and spoilage, and the supply chain behind all of it.
Pour, mix, and margin
Beverage cost and pour variance, bar inventory, spirits and distribution, brand and production economics — including a spirits company Bailiwick co-founded and helps operate.
Brands moving through other people’s shelves
Trade promotion and deductions, distributor and retailer reporting, syndicated versus shipment data, velocity by account, co-manufacturing costs, SKU rationalization, and the chargebacks nobody reconciles.
Money moving through operations
Merchant processing and interchange, effective rate analysis, settlement and deposit reconciliation, delivery remittances, chargebacks, royalty calculation, and revenue certification for lending.
What we build
Agents that do one job, provably.
Reconciliation agents
Match POS to deposits, invoices to receipts, remittances to orders — and produce an exception a controller can act on rather than a dashboard nobody opens.
Recovery agents
Find money that left the business and should not have: processor overcharges, misapplied tax, delivery fee errors, promotional deductions, royalty miscalculation.
Operator assistants
Answer above-store and store-level questions in plain language, constrained to certified metrics, with the evidence attached to every answer.
Compliance agents
Check submissions against franchise agreements, lease terms, percentage rent, and reporting obligations — continuously rather than annually.
Document and invoice agents
Read what vendors actually send — PDFs, portals, EDI, spreadsheets that change format without warning — and normalize it into something a system can trust.
Orchestration
The harder half: multiple agents with defined authority, human checkpoints, escalation paths, audit trails, and a clear answer to who is accountable when one is wrong.
Built for our own ventures first
We did not learn this on client budgets.
Everything on this page was built and hardened inside our own portfolio before it was ever offered as an engagement. That is the qualification we would want to see, so it is the one we lead with.
The consistent lesson across all of it: the agents that work are the narrow ones. Why task-specific beats one-size-fits-all →
Recovery, module by module
Separate modules for delivery fee recovery, merchant fee recovery, and franchise royalty recovery — three different reconciliation problems that share an engine and almost nothing else. The delivery module carries 83 rules; the merchant module carries 107.
A deliberately constrained assistant
Voice and text answers for operators, permitted to reason only over metrics the trust layer has already certified. It reconciles nothing. Narrowing the job that far is what makes the answers defensible.
The layer underneath all of it
A deterministic certification pipeline — no machine learning anywhere in it — running 198 governance rules and eleven trust gates, with cryptographic sealing and evidence retained end to end.
FohBoh.ai and BailiwickQuikFix are Bailiwick portfolio companies. Figures describe those products as built and are stated here to show the shape of the work, not as a benchmark for any client engagement.
How an engagement runs
Four steps, and the last one is handover.
The first three steps are the same discipline we use to build our own ventures. The fourth is where a client engagement and a venture part company: instead of launching a business, we transfer a working system to the people who will run it.
Diagnose
What decision is actually being made, who makes it, what it costs when it is wrong, and whether the underlying data can support an agent at all. Some engagements end here, and honestly.
Architect
Scope, boundaries, authority, human checkpoints, integration surface, and acceptance criteria — plus the certification requirements the MGE trust layer will enforce, written before anything is built.
Engineer
Built and hardened to production standard — security, reliability, observability, testing, and integration into the systems you already run.
Transfer
Deployed, documented, and handed to your team with the enablement to operate it. You own the system and the intellectual property in it.
What you own
The output is yours.
- You own the system and the intellectual property created specifically for you.
- It runs in your environment — your cloud, your identity, your controls.
- No lock-in by obscurity. Documented architecture, readable code, and a team that can maintain it after we leave.
- The MGE trust layer is licensed, not sold. It remains FohBoh.ai’s intellectual property, licensed to you for the life of the system on terms quoted before the engagement begins.
- Pre-existing Bailiwick frameworks remain ours, licensed to you on clear terms stated up front.
Engagements are fee-based. Where a client wants deeper alignment, we will discuss equity or a licensing structure — but that is a separate conversation and never a condition of the work.
We take client builds only where the architecture is consequential and the work sharpens our thesis.
We are not a development shop and have no interest in becoming one. We do not do staff augmentation, we do not place engineers by the seat, and we decline work where the answer is a straightforward integration someone else should do more cheaply. The engagements we want are the ones where getting the structure right is the entire difficulty — which is also the only kind where we are worth what we cost.
Have a decision that an agent could make, if the numbers held?
Tell us the decision and what it costs when it is wrong. If the data cannot support it yet, we will tell you that first.