Frontier AI is everywhere.
Reliable deployment isn't.
Agent Capital is an advisory-led AI firm for the mid-market. We start with one high-friction workflow — optimise it, find the money in it — and build a governed agent inside a harness engineered for your business.
We don't just build agents.
We find the value in your business — and use AI and automation to capture it.
Wanting AI and deploying it are two different problems.
Frontier AI is now universal and cheap. Access is no longer the advantage — reliable deployment is. Off-the-shelf tools and stretched internal teams can't ship it safely across the messy, multi-system reality of a real business. That deployment gap is what we close — with a repeatable engine, not a one-off build.
Leaders see the potential and ask for AI.
Off-the-shelf tools and stretched teams can't ship it reliably across a multi-system business.
Agent Capital bridges it →A governed agent, across your systems, your board will act on.
We climb only as far as the problem requires.
Every engagement starts with the business pain — never with a tool. We name the problem, then fix it at the lowest, cheapest, most reliable layer that solves it. The three rungs are the process; the platform and marketplace are the bedrock we can scale onto when it's worth it.
“If an agent won't pay its way, we'll tell you not to build one — and point you to a simpler fix instead. Honest advice, not an easy sell.”
Lead with revenue. Efficiency and control are the proof.
Anyone can claim efficiency. What moves a CFO to act is an agent that finds or protects money — so we lead with revenue, prove it with efficiency, and earn trust with control.
Four ways we work with you.
AI Advisory
AI-proficiency assessment — a combination of AI enablement and value creation, from strategy to the first workflow.
Explore → ServiceAgent Development & Implementation
A disciplined, repeatable build across sales, operations, finance and risk — engineered against your real data.
Explore → ServicePlatform & Marketplace
One secure home for many agents, and a growing catalogue that lets value compound over time.
Explore → ServiceAI Training & Development
Tailored programmes for Boards, Executives and Operational teams — delivered in person and online.
Explore →It already works — an analytical delivery engine, not a concept.
Take ClvrCRM, our sales-pipeline intelligence agent — one recent, now-live example. It ingests data across CRM and sales systems to surface deal velocity, staleness, weighted-average forecasts (conservative, practical and optimistic), and sales-manager and BDM performance. It's one of a growing suite of agents already in production across finance, risk, sales and operations — a delivery engine, not a concept.
The second, third and tenth agent are faster and cheaper than the first — every build feeds a flywheel.
Four ways, so value is tracked — not asserted.
Direct $$
Cost saved, revenue recovered, losses prevented — trackable on a P&L.
e.g. duplicate invoices blockedEfficiency → $$
Time and effort that convert to dollars via faster cycles or redeployed capacity.
e.g. 50–60% less MBR prep illustrativeRisk avoidance → $$
Fines, penalties and breaches avoided — expected cost × probability reduction.
e.g. card-anomaly exposure cutQualitative
Governance, consistency and capability — valuable even where it isn't a dollar figure.
e.g. board-grade audit trailFour functional areas we build for.
We build across four functions — as customised solutions specific to your business, not off-the-shelf products. Governed, and field-hardened on your real data.
Sales
Pipeline intelligence, deal velocity and forecasting — revenue you'd otherwise leave on the table.
Operations
Knowledge, policy and variance analysis — grounded in your own documents and workflows.
Finance
Month-end, cash-flow, reconciliation, spend and due diligence — analysis in minutes, not weeks.
Risk
Payroll, compliance and operational-risk work — evidenced, governed and audit-ready.
Writing on AI, finance and value creation.
Start with one workflow, not the whole platform.
Take corporate-card spend — the workflow above. Most teams eyeball a handful of transactions and miss the rest; a manual audit runs two to three days and still covers barely a third of the checks worth doing. Give us a process like that — card spend, a slow month-end, a pipeline you can't trust — and we'll map it end to end, quantify the friction, and show you the right-sized fix. Agents only where they earn their place.
Start with one workflow →We climb only as far as the problem requires.
Every engagement starts with the business pain — never with a tool. We name the problem, then fix it at the lowest, cheapest, most reliable layer that solves it. Only where judgement is genuinely needed do we build an agent.
Every workflow decomposes into three lanes.
Before a single agent is built, we split the work by who is best at each part — human, agent, or script.
Script
- Precise arithmetic
- Reconciliation
AI agent
- Pattern recognition
- Contextual reasoning
Human
- Final sign-off
- Interpreting ambiguity
The rule: the script does the maths → the agent reviews and adds judgement → the human approves.
The layers of abstraction.
The problem & symptoms
Month-end takes weeks. The same report, rebuilt every cycle. Skilled people on rote work. We map the pain before proposing anything.
Process
Map the workflow end to end and cost the friction. Sometimes the fix isn't technology at all.
Automation
If deterministic rules can do it, we automate it plainly — no agent, no model cost, no hallucination risk. We don't dress up automation as "AI".
Agentic
When the work needs judgement, we engineer an agent — not a prompt. Select (scored, and we'll tell you not to build if it doesn't earn its place), architect, guard, test, deploy.
Platform Enterprise option
One secure home for many agents — multi-tenant, isolated per session, data masked at source, model-agnostic. Hosted on our cloud or yours.
Marketplace Direction of travel
A growing catalogue of productised agents — ours, and eventually agents built by others. Value compounds; context becomes the switching cost.
“If an agent won't pay its way, we'll tell you not to build one — and point you to a simpler fix instead. Honest advice, not an easy sell.”
We only build where it's worth building.
Every candidate use case is scored across five dimensions out of 25. We proceed only above the threshold — discipline before enthusiasm. The scores below are the actual evaluation of an agent we built and now run in production.
The harness: our IP, wrapped around every agent.
Anyone can build an agent — the model is a commodity. The hard part, and our IP, is the harness it runs inside: the client-specific context and the controls, engineered to your business so a board will act on the output. Your team and ours stay accountable at every step.
Building the harness is a heavily analytical exercise. We engineer the client-specific context and a layered set of controls — anti-hallucination, evidence and citation on every finding, human approval by risk tier, scope discipline, escalation triggers and an immutable audit trail — against your real, messy data, then stress-test the agent until its output is board-grade rather than a black box.
A structured approach to agent development and deployment.
Every agent follows the same repeatable, six-phase playbook — from problem selection through to scaled deployment. Discipline at each phase is what makes the output board-grade rather than a demo.
Select
Score each candidate. Below the bar, we say no.
Map
Split the work into human, agent and script lanes.
Build
Engineer the agent — a real architecture, not a prompt.
Guard
Wrap it in our harness — the controls that make it board-grade.
Test
Prove it on real, messy data before it ships.
Deploy
Shadow mode first, then scale with monitoring.
The flywheel: every deployment feeds the next — defects become test cases, patterns become reusable skills, friction becomes documentation.
Corporate-card anomaly audit.
Here is a real one — ClvrSpend, our corporate-card anomaly agent — mapped the way we would map yours. Five phases across three lanes (human judgement, agent interpretation, deterministic automation), with the friction and the right-sized resolution named at every step.
Data ingestion & field mapping
AIAiHumanSix-domain anomaly detection — 38 checks
AI coreRisk scoring, profiling & exposure
AI coreThree-tier report generation — 9 sections
AI draftHuman QAInvestigation & remediation
Human ledAI assistAll 38 in a single pass — a manual audit does ~12.
Roughly 90% faster.
Automation 8% — Excel filters.
AI 2% — none / ad-hoc.
Roughly 12 of 38 possible checks performed.
AI agent 65% — 38 checks, scoring, reports, case packs.
Automation 15% — parsing, mapping, formatting.
Full forensic-grade analysis; recurring offenders tracked.
/ Cycle time 2–3 days → 2–3 hours · roughly 90% faster, with every critical finding evidenced.
Every agent is tied to a measurable return.
Classified four ways, so value is tracked — not asserted.
Direct $$
Cost saved, revenue recovered, losses prevented — trackable on a P&L.
e.g. duplicate invoices blockedEfficiency → $$
Time and effort that convert to dollars via faster cycles or redeployed capacity.
e.g. 50–60% less MBR prep illustrativeRisk avoidance → $$
Fines, penalties and breaches avoided — expected cost × probability reduction.
e.g. card-anomaly exposure cutQualitative
Governance, consistency and capability — valuable even where it isn't a dollar figure.
e.g. board-grade audit trailStart with one workflow, not the whole platform.
Give us one process that frustrates you — a slow month-end, a report rebuilt every cycle. We'll map it, find the friction, and show you the right-sized fix. Agents only where they earn their place.
Start with one workflow →Four ways we work with you.
From finding the value to governing it in production. Each engagement leads with revenue; efficiency and control are the proof.
From business problem to measured return.
One philosophy runs through every service line, and it applies to all engagements: we start with the business problem, fix it at the right layer, and track the return — never technology for its own sake.
Diagnose
Advisory finds where money leaks or hides in your operations.
Map
The workflow, end to end — split into human, agent and script lanes; friction costed.
Right-size
Process change, plain automation, or an agent — scored, so you only build what earns its place.
Build & govern
Engineered against your real data, with guardrails, testing and staged rollout.
Measure
Return tracked four ways — money, efficiency, risk avoided, and capability.
AI Advisory
An AI-proficiency assessment that combines AI enablement and value creation — we find where money leaks or hides in your operations, and set the strategy, policy and business case to act on it. The front door to everything else.
- AI-proficiency assessment and roadmap
- AI enablement — strategy, operating model and AI-use policy
- Value creation — friction mapped and costed, revenue found or protected
Agent Development & Implementation
A disciplined, repeatable build across your business functions — sales, operations, finance and risk — engineered against your real, messy data, not in a vacuum, and stood up in production with governance.
- Use-case scoring and selection
- Four-layer agent architecture with guardrails
- Golden-set testing and staged deployment
Platform & Marketplace
One secure, enterprise-grade home for many agents — isolated per session, data masked at source, model-agnostic — and a growing marketplace catalogue, so value compounds as more of your work is mapped in.
- Secure, multi-tenant platform hosting — our cloud or yours
- A catalogue of productised agents, plus bring-your-own
- Governance, usage controls and flexible commercials
AI Training & Development
Tailored programmes for Boards, Executives and Operational teams — delivered in person and online, hands-on right down to demonstrations from your phone — so your people can govern and get value from AI, not just admire it.
- Board and executive briefings
- Operational team enablement
- Delivered in person and online
Three things a single-vendor platform can't give you.
Across your systems
We orchestrate agents across the systems you already run — ERP, CRM, spreadsheets, systems of record — reasoning over the combinations no single platform can see.
Model-agnostic by design
We route to the best, cheapest or most accurate model for each task — and swap frontier for open-weight without re-plumbing. Choice is the product, not a feature.
Built by practitioners
Former CFOs and M&A partners who've run these functions — not junior consultants over a subcontracted build. Board-grade, not a black box.
Across your systems — not inside one vendor's walls.
…and all your data has to move in.
Two ways in — both start with one workflow.
Not sure where the value is? Start with an advisory diagnostic and we'll find where money leaks or hides. Already know the workflow? We'll build the governed agent to fix it. Either way we start small and prove the return before scaling.
A growing suite of productised agents.
Purpose-built, governed, and field-hardened on real data — across sales, operations, finance and risk. All are in production; new agents are added as we solve real client problems.
Sales pipeline intelligence — flags deals slipping and revenue at risk.
Policy & procedure knowledge base — answers grounded in your own documents.
AI-use & governance policy drafting and compliance mapping.
Insurance claims variance analysis.
Monthly Business Review & analysis — variance, narrative, board-ready reporting.
Cash-flow analysis & forecasting.
Accounts-payable anomaly detection & reconciliation.
Deal due diligence (financial DD).
Corporate-card anomaly detection.
Payroll & wage compliance.
Aged-care quality & compliance.
APRA operational-risk compliance (CPS 230 / 234).
Bring an agent; we host, govern and scale it.
Every agent ships with anti-hallucination controls, evidence-and-citation on every finding, human sign-off by risk tier, and an immutable audit trail. Board-grade, not a black box.
See an agent run on your own data.
Pick the agent closest to a problem you have — or bring your own. We'll pilot it on a single workflow, governed and audited from day one, so you can judge it on your numbers, not a demo.
Request a pilot →The enterprise-grade AI platform, purpose-built for your agents.
Zero sovereignty compromise. Built on security. One secure home for many agents — and a growing marketplace that lets value compound over time.
The core differences from a consumer chatbot.
Four principles set the platform apart before you even reach the pillars — the things a chatbot with a login can't give a finance or risk team.
Edge data masking
Sensitive finance parameters never leave your local VPC. Data is mapped to anonymous tokens before any prompt reaches our AI router.
Ephemeral isolation
Every analysis session spins up its own isolated runtime, destroyed on logout or exit. No multi-tenant spillover possible.
Enterprise packaging
A fully engineered multi-tenant portal with robust access management, granular audit logs, and out-of-the-box storage integrations.
True sovereignty
Because sensitive data never resides on our cloud, it can't be compelled from us — structural protection against extraterritorial data-access demands.
Eight pillars, one secure platform.
A short summary of how each pillar works — from local privacy shielding to per-session isolation, governance and telemetry.
Privacy shield
A local microservice inside your VPC masks sensitive PII — names, tax IDs, banking details — before any prompt reaches our AI router. Decryption happens locally, so raw data never enters our system.
Secure ingestion
Out-of-box coverage masks standard PII categories with no configuration. Two modes: a pre-masked local vault, or VPC drag-and-drop routed through local sanitisers before execution.
Session isolation
Every click on "Analyse" deploys a temporary, sandboxed container dedicated to that task alone. No persistence, no cross-contamination, zero cache leakage between team members.
Mission control admin
A central governance panel where admins manage tenant permissions, turn limits, model overrides and live billing — with SSO and real-time usage tracking, from a pilot team to thousands of users.
Execution theatre
A secure workspace with side navigation across your entitled Clvr agents. Teams run multi-turn analysis, monitor quota at a glance, and work across parallel agent sessions at once.
Usage & quotas
Two-layer quota control — monthly allocations per user, and per-session turn limits — prevents runaway usage and contextual drift, with visual alerts as a session approaches its limit.
Security guardrails
Every input is screened inside the application layer before it reaches the model: prevention (strip injection payloads), detection (intent & topic-drift analysis), and remediation (rollback context to protect session limits).
Usage & telemetry
Real-time telemetry tracks masked-token volume and usage trends across active deployments, piped into a central data warehouse for transparent, auditable reporting.
Extensibility roadmap
A staged path from pilot to scale: user pilot, then integration with company storage, then customisation of prompts and directories, then sovereign scale with custom LLM backends.
Deployed your way.
Two ways to run the platform, depending on how much of the boundary you need to own.
Direct Sovereign Cloud
Run via our highly scalable core system. Orchestration allocates temporary sandboxes on demand — no infrastructure for you to manage, while sensitive parsing stays in your self-hosted VPC.
Hybrid Sovereign Mesh
For organisations requiring complete internal computing boundaries. Deploy the edge data utility and the sandboxed ephemeral pods directly inside your own cloud (AWS or GCP).
Mapped to the standards your board answers to.
The platform is designed to support the frameworks a finance and risk function is accountable for — with the controls, isolation and audit trails they call for.
ISO 42001
System configurations, active guardrails, prompt boundaries and token-tracking audits mapped to the international AI-management standard.
APRA CPS 230 / 234
Provider-agnostic routing, isolated per-session processing and explicit human-action audit trails, supporting operational-risk and information-security obligations.
EU AI Act
Documented turn limits, audit trails and human-in-the-loop checkpoints to support oversight of higher-risk operations.
The platform opens up — and value compounds.
A growing catalogue of productised agents — ours, and eventually agents built by others — already taking shape across finance, risk and operations.
Finance
Close & MBR, forecasting, reconciliation, deal diligence and spend controls.
Risk
Compliance and operational-risk monitoring, mapped to the standards your board answers to.
Sales & Operations
Pipeline intelligence, grounded knowledge, governance policy and claims workflows.
Bring your own
Bring an agent; we host, govern and scale it — with third-party agents joining over time.
Twelve productised agents in production today, and growing — each detailed in the agent suite.
See the full agent suite →Why the position compounds.
Accumulated context
Once your business is mapped into the platform, that context is the switching cost. We become the layer downstream processes depend on.
Built in the trenches
Agents are engineered against real, messy data — not in a vacuum. That field-hardening is what generic tools skip.
Auditability
Full lineage on why an agent did what it did. In regulated settings, a black box is a liability — traceability is the product.
Let's build a secure, sovereign AI platform for your business.
Start with one workflow and a single agent, or scope the platform for many. We'll show you the right-sized path — and the controls your board will want to see first.
Book a consultation →AI capability, delivered in person and online.
A structured, assessed AI training programme for boards, executives and the people doing the work — facilitated in the room, or taken self-paced online. Everyone is placed at the right depth, assessed against a common core, and certified.
In person, online, or both.
One programme, two delivery modes — run them together for a full rollout, or start with whichever fits the room.
Facilitated sessions
Board, executive and practitioner sessions run live — hands-on where it counts, working on your own material, with the governance rules applied in real time.
Self-paced & assessed
The same programme as a responsive online course people take at their own pace, on any device — placement, teaching, a knowledge check and a certificate at the end.
The same programme, on any device.
Self-paced, placement-based and assessed — delivered responsively across desktop, tablet and mobile, so a whole workforce can complete it wherever they work.
A demonstration build of the self-paced programme. Learners are placed, taught at their depth, checked and certified.
Eight pillars — what every organisation must get right about AI.
A fixed order — mechanics before governance, because you can't set a sensible rule for a system you can't reason about.
Foundations
What AI actually is, and how it fails.
The Value Case
Where AI earns its place — and where it doesn't.
Tools & Platforms
The landscape, and how to choose inside it.
Agentic AI
When AI stops answering and starts acting.
Data, Privacy & Security
Where your information actually goes.
Governance & Accountability
Who owns it when it goes wrong.
Standards & Compliance
ISO 42001, NIST AI RMF and the obligations already live.
Adoption & Change
Getting from pilot to practice on the floor.
One programme, three depths.
Everyone covers the same eight pillars. A short questionnaire places each person at a starting depth — placement, not grading. It's a routing suggestion, not a score, and people can move up or down at any time.
Know what to ask
Know the vocabulary and the failure modes — enough to ask a good question and judge the answer.
Interrogate it
Use AI on real work, challenge its output, and know where your data went — the practical consequences.
Shape and control it
Design and govern how AI is used — the resourcing, controls and accountability implications.
One spine, four audiences.
Differentiated by decision right, not by difficulty — a board and a care manager need the same pillars for entirely different reasons.
Boards & governing bodies
The questions to put to management, and the test for judging the answers — bolted onto an existing board meeting.
Executives
A value map across your functions and a costed, 90-day plan the executive team owns — built in the room.
Operational teams
A reviewed workflow, a claim-interrogation habit, and a data-handling rule people will actually follow.
All staff
A certified baseline the organisation can evidence across the whole workforce, taken online at each person's pace.
Assessed, certified, and kept current.
The difference between a training day and a capability programme is what survives it — a comparable result and a record you can stand behind.
Placement, not grading
A short questionnaire sets each person's starting depth. Taken once, never used to rank.
Assessed common core
Every participant answers the same core, so a cohort's results stay comparable.
Individual certificate
A record of what was covered, at what depth — with the full private breakdown kept to the learner.
Quarterly refresh
Content is re-verified and updated each quarter, so the programme doesn't go stale.
The same spine, tuned to your sector.
The examples, cases and regulatory layer swap for your world — in aged care, for instance, that means the Aged Care Act, the strengthened Standards and incident reporting, with cases drawn from documentation, incident triage and family communication. Sector tailoring is a swap, not a rebuild, so a second sector is weeks, not months.
Bring AI capability to your team.
Run a board or executive session, roll the self-paced programme across your workforce, or both. Tell us who needs to be capable and by when, and we'll shape the right mix of in-person and online.
Talk to us about training →We've run the functions we now build for.
Agent Capital is an advisory-led AI value-creation firm. Our team comprises experienced industry veterans with deep experience in business and technology transformations.
Practitioner depth, not a subcontracted build.
Agent Capital exists because the deployment gap is a practitioner problem. We've run the sales, operations, finance and risk functions we now build for — which is why our agents are engineered for the real world, not the demo.
The firm is led by two complementary founders: value creation and finance on one side; operations, growth and delivery on the other — a clean split that lets us both find the value and stand it up reliably.
Complementary, not overlapping — we both find the value and stand it up reliably.
The people who do the work.
Two complementary founders — value creation and finance on one side; operations, growth and delivery on the other — backed by a team of deep functional and technical consultants who engineer and stand up the work.
Dushyant Kapoor
Value creation and finance — a former CFO and value-creation practice leader who has run the finance and transformation functions we now build for.
Let's see if we're the right fit.
We work best with teams who have one frustrating workflow and a real number attached to it. If that's you, a short conversation is the fastest way to find out whether we can help.
Start a conversation →Writing on AI, finance and value creation.
Field notes from our co-founder Dushyant Kapoor on deploying AI where it earns its place — governance, model choice, finance transformation and the deployment gap.
The change management nobody's budgeting for
Why the hardest line item in an AI rollout isn't the licence or the training — it's being straight with people about what's uncertain.
Read on LinkedIn →ArticleYou don't need the latest model — you need the right one!
Most business tasks don't need the newest, biggest model. On choosing the right-sized model — and running smaller open models yourself.
Read on LinkedIn →ArticleThe three AI governance questions every board should be asking
Beyond a policy written by legal and a committee that never meets: the three questions directors should keep asking about AI.
Read on LinkedIn →ArticleA little knowledge and a lot of confidence
A pilot can dazzle a board; implementing an agent into a real workflow is a different undertaking entirely.
Read on LinkedIn →ArticleYour finance team isn't under-resourced — it is mis-resourced
Finance teams aren't short of people. Most time goes on maintenance work instead of the analysis that moves the business.
Read on LinkedIn →ArticleCFOs must govern AI agents for finance
As the interaction layer shifts to agents, governing what they do in your finance systems is a fiduciary question, not a technical one.
Read on LinkedIn →ArticleHeadless Enterprise Software: what it means for finance leaders
Enterprise software is splitting in two — systems of record stay, the interaction layer moves to agents. What that means for finance.
Read on LinkedIn →ArticleIn 100 days, you pull 3–5 value-creation levers. What if you could pull 8–10?
AI shifts the economics of investigation — so a value-creation team can pressure-test far more levers than the classic handful.
Read on LinkedIn →Published on LinkedIn by Dushyant Kapoor. Follow along on LinkedIn →
Start with one workflow.
Give us one process that frustrates you — a slow month-end, spend that isn't reviewed, a pipeline you can't trust. Reach either of us directly and we'll take it from there.