Plus $5.0M growth capital; optional $5.0M milestone tranche.
Internal draft | Investment memoEnergy operations context, mispriced
Entry valuation$6.0M EV base Hold frame5-7 year build Upside casePlatform re-rating
Energy operations context, mispriced
as
workflow
software.
Garner is best understood as a hard-to-replicate operational context layer inside oil and gas supply-chain workflows, with a credible path to become a system of action rather than a conventional workflow tool.
The downside can be underwritten to concentrated recurring durability; the upside is linked to labor-budget AI monetization, margin structure improvement, and selective expansion rather than a single speculative leap.
Value creation tied to contract economics and operating execution.
Triggered by AI pricing proof, renewal leverage, and concentration reduction.
01 | Executive summaryWhat is provenEnterprise embedment and workflow usage. What must be provenRepeatable AI monetization and new-logo motion. What creates valueCommercial reconstruction, not invention.
A concentrated asset with unusually asymmetric context value.
Garner is a concentrated vertical workflow asset with deep embedment in high-consequence energy operations. The core investment insight is that the company has already secured the hardest substrate for vertical AI: trusted position inside live work, with operational context accumulated across real enterprise workflows.
The right underwrite is sober. Pay for current recurring quality and structural stickiness. Treat AI, value-based pricing, and multiple expansion as earned upside that must be released through milestone discipline.
Chevron and Exxon Mobil relationships, MSA access, active user footprint, and workflow history reduce pure market adoption risk.
The underwriting work is to convert existing context depth into packaged modules, measurable outcomes, and a repeatable commercial motion.
Pricing, packaging, account expansion, workflow standardization, and AI module monetization matter more than a wholesale product rebuild.
Acronyms, shorthand, and memo language in one place.
This layer keeps the memo readable without forcing every section to restate diligence language, sponsor shorthand, or industry terminology.
Acronyms
ARR
Annual recurring revenue. In this memo, true ARR is separated from services and project-linked revenue.
AWP
Advanced Work Packaging, a capital project operating framework for sequencing materials, tasks, and readiness.
IOC / NOC
International Oil Company and National Oil Company; the main enterprise customer classes in this thesis.
MSA
Master Service Agreement. A major diligence point because existing Chevron and Exxon Mobil access lowers adoption friction.
POC
Pilot or proof-of-concept, ideally reframed as a paid diagnostic that quantifies operational leakage.
Investor shorthand
Context layer
The integrated operational memory across systems, vendors, documents, statuses, exceptions, and decisions.
System of action
A platform that routes, resolves, and eventually executes work rather than only reporting status to humans.
Clone test
Would a new AI-first entrant beat Garner without Garner's historical workflow data and enterprise trust?
Labor-budget pricing
Commercial framing tied to operating cost, cycle time, and throughput rather than IT software spend.
Generative moat
A learning loop where every resolved exception, vendor pattern, and human override improves the platform.
03 | The problem
Energy work breaks between systems, not inside one system.
Energy operators already have ERP, procurement, project, maintenance, freight, vendor, and document systems. The unsolved problem is what happens across them: email threads, missing documents, late inspections, vendor responses, material readiness, invoice inquiries, and cross-BU knowledge that never becomes reusable operating memory.
ERP blind spot
ERP records the official transaction. It often does not explain why the workflow failed, where the delay originated, or which party actually caused the problem.
What operators see
A vendor missed a promise date.
What Garner can surface
The late inspection request created the delay.
Information asymmetry
One business unit can solve a customs, supplier, or material issue while another repeats the same mistake because the resolution was never captured in a shared workflow layer.
Cost shape
Rework, idle resources, delay claims, and duplicate procurement.
Investment relevance
Persistent pain supports recurring platform value.
Manual exception work
Invoice inquiries, shipment exceptions, vendor follow-ups, and document gaps still rely on human routing and institutional memory.
Why AI matters
Unstructured work can now be classified, routed, and resolved.
Why Garner matters
The context layer already sits where that work happens.
04 | Solution and productCurrent stateLive in complex supermajor operations with configurable workflow logic. Target stateSystem of action with priced outcome modules layered on context. Key testCan context depth translate into durable pricing power?
A context layer that exposes action queues, not another dashboard.
Garner aggregates process context across ERP records, vendor communication, logistics artifacts, and workflow ownership, then exposes action queues by role. Operationally, it answers: what needs action now, by whom, and with what evidence.
The current footprint is anchored in order, material, and payment workflows, with early AI modules oriented around inquiry handling, document matching, and anomaly detection.
Garner Frontier architecture1
The target state is a governed system of action, not a dashboard layer.
Control
Enterprise governance
Role permissions, auditability, data-boundary controls, model routing, and human approval thresholds.
Layer 6
Interfaces
Role-specific surfaces for every operating persona, from field supervisor to executive sponsor.
Layer 5
Workflow execution
Agents classify, match, route, escalate, and eventually execute narrow trusted actions.
Layer 4
Evaluation and optimization
Override tracking, accuracy loops, resolution quality, and ROI instrumentation.
Layer 3
Domain intelligence
Energy-specific reasoning over shipment, invoice, material, vendor, and project workflows.
Layer 2
Business context layer
Workflow state, decision history, documents, comments, operational metadata, and vendor behavior.
Layer 1
Systems of record integration
ERP, procurement, maintenance, freight, vendor, email, document, and project systems.
1 More detailed architecture can be found in Section 17, Future Platform Architecture.
05 | Why nowLabor budget over IT budget Stay in the work Compounding data moat Terrain advantage
AI is moving from pilot chat to workflow execution.
Enterprise buyers are shifting from generic AI experimentation to workflow-level automation with governance. In this phase, context quality and process ownership matter more than model novelty.
Garner's advantage is timing: the workflow structure is already in place while market pricing still reflects niche workflow software economics.
Agent deployment requires structured contextHigh relevance
Industrial workflow complexity persistsSustained
Narrative-to-value gap still openEntry window
Commercial value should be benchmarked to avoided labor and delay costs, not software line-item spend.
Winning platforms execute decisions in workflow, rather than only visualizing status for humans.
The feedback loop from live operations should improve model judgment every cycle and widen defensibility.
Regulatory and procedural complexity in energy creates high barriers for horizontal entrants.
06 | Market opportunityFocused wedge: high-
Focused wedge: high-
consequence
operators with
fragmented execution
The relevant market is not generic workflow software. It is complex industrial operations where process failures have outsized cost and where execution spans internal and external parties.
Commercially, this is a depth-first strategy: fewer accounts, larger ACV, multi-year expansion inside each operator.
Supermajors
Highest near-term value because Garner already has Chevron and Exxon Mobil proof. Expansion matters before broad prospecting.
Why it fits
Large leakage, complex workflows, long operational memory.
Commercial shape
High ACV, long cycle, high switching friction.
EPC channel
EPCs can accelerate project-level adoption if Garner becomes the interface owners expect contractors to use.
Why it fits
Project control, material readiness, document mismatch pain.
Commercial shape
Potentially faster cycle and channel leverage.
NOCs
NOCs are strategically attractive but slower. Government procurement, data sovereignty, and local content requirements make sequencing important.
Why it fits
Similar project complexity and institutional memory issues.
Commercial shape
High value, relationship-led, 24-36 month path.
Adjacent heavy industry
Industrial verticals with complex assets, constrained labor, and fragmented field-to-office workflows may become attractive once energy proof is packaged.
Why it fits
Similar coordination failures, compliance intensity, and high cost of downtime.
Commercial shape
Secondary expansion path after supermajor proof; likely narrower initial wedge.
07 | Business modelTrue ARR$2.34M FY26E revenue$3.50M USD Services / project$1.16M Collection profile70% today
Recurring platform economics, blurred by services and underpricing.
The current business blends recurring license revenue with services and project revenue. That mix creates valuation noise, but it also creates the entry opportunity: underwrite the quality-adjusted recurring base, then productize recurring workflows and price AI/outcome modules separately.
Primary valuation anchor after excluding episodic services.
Converted from C$4.8M projection; includes services mix.
Real revenue, but lower-quality for software valuation.
Current contracted revenue visibility; revenue classification still requires diligence.
08 | Financial profile and valuation
Numbers support the entry case, not the full rerating.
The entry valuation should be anchored to current recurring ARR and services revenue, with growth capital structured separately so upside is earned through product, AI, renewal, and new-logo milestones.
Revenue quality progression
Illustrative mix shift from current blended revenue toward a higher recurring profile.
$3.50MFY2026E revenue baseline
$0.80MAdjusted EBITDA baseline
Scenario lens3
Scenarios frame the underwriting range and the milestones required to earn each outcome.
$10M-$15M
0.9x-1.4xMOIC on $11M initial capital
Primary $5.0M growth capital is deployed, but no AI pricing, no new logos, and limited renewal leverage keep exit value near capital preservation.
Interpretation
Downside assumes the capital improves product readiness but does not yet earn a platform multiple or solve concentration.
$40M-$55M
3.6x-5.0xMOIC on $11M initial capital
Initial $11.0M total capital supports Chevron AI amendment, one new logo, and renewal repricing, creating a roughly 3.6-5.0x outcome if execution holds.
Interpretation
The deal works if Chevron repricing, AI packaging, and one credible new-logo path convert the current substrate into priced execution.
$220M-$300M
13.8x-18.8xMOIC on $16M fully depl. capital
Assumes the optional additional $5.0M is released after milestones, with full AI platform proof, target Chevron renewal economics, and three supermajors by FY2030.
Interpretation
The upside case should be higher, not lower, if incremental capital funds the proof required to earn a true platform rerating.
Entry valuation bridge2
Disciplined entry separates current revenue value from growth capital and earned optionality.
ComponentReferenceMultipleValue
ARR base
$2.34M
2.3x$5.4MServices base
$1.16M
0.5x$0.6MARR + services
$3.50M
-$6.0MARR-only read
$2.34M
2.6x$6.0MEBITDA read
$0.80M
7.5x$6.0MCapital plan: $5.0M primary growth capital on balance at close, with an optional additional $5.0M released only against milestones.
Sensitivity map
The model is most sensitive to renewal economics and concentration reduction speed.
Chevron repricingVery high
New-logo conversionHigh
AI module pricingHigh
Opex disciplineModerate
Underwriting implications
Renewal pricing is the first-order driver.
Chevron repricing should be treated as the primary value unlock, not a nice-to-have.
Diversification is the risk reducer.
A second scaled logo changes the concentration discount more than marginal ARR growth.
AI pricing must be evidenced.
Module pricing should follow measurable labor, cycle-time, or exception-resolution outcomes.
2 Entry EV is triangulated three ways: $2.34M ARR at 2.3x plus $1.16M services at 0.5x; $2.34M ARR only at 2.6x; and 7.5x on $0.80M EBITDA. Each lens supports approximately $6.0M enterprise value before primary growth capital. Financial statements are compiled, not audited.
3 Illustrative exit value ranges based on current draft underwriting assumptions. Values represent potential exit enterprise value, not net proceeds. MOIC uses $11.0M total initial capital for downside/base outcomes and $16.0M fully deployed capital for the upside case if the optional $5.0M milestone tranche is funded. Real-life outcomes may differ as diligence, model work, market conditions, and execution milestones progress.
09 | Customer traction and proof points
The proof is depth, not breadth.
Garner's installed base is concentrated, but the account quality is unusual. The strongest proof is not logo count; it is enterprise trust, workflow depth, and the fact that large operators use Garner for real operating work.
Chevron
Enterprise-standard footprint across multiple business units, 21.6k user reference, workflow overage, and AI roadmap relevance. Strongest account proof and highest near-term repricing lever.
Exxon Mobil4
Long tenure and GarnerSurplus history support the institutional trust argument, but expansion requires a VP-level sponsor and value-based repricing discipline.
Platform scale
Materials cite 3B material transactions, 275M shipment records, 500+ supply chains, 93k vendors, and 15 countries. These scale markers are central to the context-layer thesis and should be treated as priority confirmation items.
4 Seplat became part of the Garner customer picture through Exxon Mobil's divestment of its Nigerian JV assets. The logo should therefore be read less as an independently sourced new-logo win and more as continuity evidence: Garner workflows, data, and operating context can persist through asset ownership transition when the underlying operational need remains intact.
10 | Competitive positioning
The market rewards the story Garner has not yet told.
AI-native procurement/workflow entrants show the market is willing to fund agentic workflow automation. Garner's edge is that it already has the context layer those entrants are trying to build; the opportunity is to package and commercialize that edge with comparable clarity.
Against ERP
ERP is the system of record for transactions. Garner can become the system of record for what actually happens across parties.
Garner advantage
Workflow context and exception history.
Underwriting focus
Repeatable integration and deployment speed.
Against AI entrants
New entrants may ship faster and message better, but they lack years of supermajor context and trust.
Garner advantage
Embedded operational memory.
Underwriting focus
Packaging velocity and UX modernization.
Against services firms
Systems integrators can build workflow solutions, but they do not own a repeatable context product unless Garner fails to productize.
Garner advantage
Reusable workflow primitives.
Underwriting focus
Services mix versus reusable product work.
11 | Growth strategy and value creation plan90-day product proofModernize workflows and instrument AI feedback Commercial reframingPrice against labor and delay outcomes 6-12 month moatBuild the cross-customer signal layer Implementation playbookCodify deployment governance Margin controlReduce AI cost and infrastructure leakage Platform positioningShift from workflow tool to system of action GTM engineBuild repeatable enterprise commercialization Energy Center of ExcellenceUse executives to validate and open the market
Protect anchor, monetize AI, then prove replication.
Value creation requires sequence discipline. The first phase should de-risk anchor economics, leadership continuity, and product readiness before broad logo expansion. Pricing amendments should follow UI/UX improvement, AI module proof, workflow standardization, measurable outcome evidence, and a more institutional GTM engine supported by energy executive advisory credibility.
0-6 monthsDe-risk
Lock key retention, install dedicated account leadership, complete contract/evidence diligence, and modernize priority UI/UX workflows.
6-18 monthsMonetize
Prove AI modules in live workflows, standardize top workflows into repeatable templates, then execute pricing amendments tied to measured outcomes.
18-36 monthsReplicate
Land one new enterprise logo and reduce concentration ahead of the renewal inflection.
Upgrade priority screens, standardize core order/material/payment workflows, and capture every override, resolution, and prediction outcome.
Move AI modules from IT tooling to operating-budget protection, with pricing tied to measurable cycle-time, rework, and exception-resolution savings.
Develop anonymized benchmarking around vendor risk, exception patterns, and resolution quality while preserving customer data boundaries.
Define roles, data boundaries, approval thresholds, and rollout steps so AI-enabled workflows can scale without bespoke implementation drag.
Route routine tasks to lower-cost models, reserve frontier models for complex reasoning, and recover cloud spend through workflow-level pricing.
Reframe Garner as an energy execution platform that absorbs function over time, not simply a dashboard or assisted workflow layer.
Move from relationship-led selling to account-based coverage across supermajors, EPC channels, and complex energy operators.
Stand up an advisory layer of energy operators to pressure-test modules, sharpen ROI claims, and create senior-buyer credibility.
12 | Risks and underwriting considerations
The risks are real, specific, and manageable only with structure.
Garner is small, concentrated, commercially underbuilt, and dependent on technical/customer continuity. Those risks are acceptable only if the entry price, structure, and post-close plan reflect them.
Concentration
Two customers account for most value. Mitigation is not wishful logo expansion; it is Chevron durability, Exxon expansion, and one credible new-logo path within 24 months.
HighKey person
Technical/customer continuity around the incumbent product, implementation knowledge, and customer relationships is a critical diligence and deal-structure item. Retention should be a gate, not an integration footnote.
HighImplementation
Configurability may be a platform strength or a services trap. Diligence must separate configuration, implementation, custom development, and reusable product work.
MediumAI monetization
The architecture is AI-ready, but commercial proof requires priced modules, measurable outcomes, and governed execution rights.
MediumReporting quality
Financial statements are compiled rather than audited, and revenue classification needs reconciliation before any multiple is applied.
Medium13 | The Ask
Clean up the balance sheet, align stakeholders, and fund the value-creation plan.
The proposed financing should separate what is being bought today from what must be earned through execution. The ask is designed to remove legacy balance-sheet and cap-table overhang, retain critical continuity, and put growth capital behind product, AI, and commercial milestones.
Immediate package$11.0M
$4.0M PIK debt plus $2.0M retention note / rollover plus $5.0M growth equity.
Milestone capacity+$5.0M
Optional tranche released only against clearly defined operating and commercial proof points.
PIK debt$4.0M
Use of proceeds
Refinance approximately $3.0M of balance-sheet debt, repay legacy investors, and simplify the cap table.
Investor logic
Removes overhang while preserving cash for operations.
Retention note + rollover$2.0M
Use of proceeds
Align key stakeholders through transition and preserve product, customer, and implementation continuity.
Investor logic
Makes continuity an explicit deal-structure item rather than an integration assumption.
Growth equity$5.0M
Use of proceeds
Fund UI/UX modernization, AI module proof, workflow standardization, account leadership, and GTM buildout.
Investor logic
Capital goes on balance sheet to earn the platform case, not inflate the entry valuation.
Optional milestone tranche$5.0M
Use of proceeds
Additional equity or note capacity released only after agreed milestones are met.
Investor logic
Protects investors from funding aspiration before evidence while preserving upside capacity if execution is working.
14 | Closing investment thesisProceed ifEntry price and structure reflect current risk. Create value byTurning operating context into priced outcomes. Do not proceed ifThe platform is mostly bespoke implementation work.
Buy the context foundation; earn the platform rerating.
Mispricing is the opening. Garner is attractive because it owns a rare operational context asset inside a vertical where trust, workflow position, and historical process data are hard to replicate. The asset is mispriced because it has been framed and monetized like workflow software rather than an execution layer for energy operations.
The underwrite is layered. The entry case is grounded in current ARR, services value, and adjusted EBITDA support. The upside case is earned through pricing, product packaging, workflow standardization, AI module monetization, customer expansion, and commercial leadership.
The exit story is plausible, not automatic. Garner is not yet a scaled AI-native platform. But if product proof emerges and the business reduces concentration while converting context into priced outcomes, the asset should be viewed differently by both financial and strategic buyers.
Target $6.0M EV, with $5.0M primary growth capital funded on balance and an optional additional $5.0M released only against milestones.
Attach AI modules, price against labor and delay, and standardize workflows into repeatable products.
If new deployments require repeated custom logic, the software rerating thesis weakens materially.
15 | FAQ
Selected investor questions drawn from diligence responses.
This section summarizes the questions likely to come up first in IC, reframed into concise investor-facing answers for ease of reference.
Is this a workflow software deal or an AI platform deal?+
Today it is under-monetized workflow software with embedded operating context. The thesis is to convert that installed context asset into AI execution economics through priced modules, workflow templates, and measurable labor or cycle-time outcomes.
What is the single biggest risk?+
Customer concentration remains the primary underwriting risk until renewal pricing and logo diversification milestones are delivered. The mitigation is not broad prospecting for its own sake; it is Chevron durability, Exxon expansion, and at least one credible new-logo path inside 24-36 months.
Why can this be defensible against new entrants?+
New entrants can replicate interfaces faster than they can replicate embedded operational context, approval history, exception-resolution memory, and trust inside complex energy workflows. Garner's moat must become productized, but the raw substrate is already difficult to recreate.
What proves the case in the first year?+
Retention of key operators, UI/workflow modernization, first AI module proof in live workflows, and a pricing amendment tied to measurable operating outcomes. The year-one goal is not narrative expansion; it is evidence that context can become priced execution.
What does the $6.0M entry valuation actually underwrite?+
The entry value underwrites the current revenue base. It can be triangulated as $2.34M ARR at 2.3x plus $1.16M services at 0.5x, or as an ARR-only read at 2.6x, with $0.80M adjusted EBITDA implying a 7.5x cross-check. The $5.0M primary growth capital is separate and should fund product, AI, and commercial execution rather than inflate entry value.
Why is the optional additional $5.0M milestone-based?+
The follow-on capital should be earned by proof, not committed against aspiration. Release gates should include AI module adoption, renewal uplift, implementation repeatability, leadership continuity, and evidence of a second scaled logo path.
How should investors interpret Seplat?+
Seplat should be read as continuity evidence, not a clean new-logo win. The relationship became relevant through Exxon Mobil's Nigerian JV asset divestment, which supports the idea that Garner workflows and context can persist when asset ownership changes and the operating need remains.
What is the evidence that software can scale outside bundled services?+
The current evidence is strongest in workflow depth and customer embedment, not yet in standalone software scalability. The underwriting question is whether configurable logic can be converted into repeatable modules, implementation playbooks, and outcome pricing without requiring bespoke services each time.
Does Garner need to become a broad horizontal platform?+
No. The attractive path is a focused vertical wedge: high-consequence energy operators with fragmented execution across ERP, procurement, logistics, vendor communication, and payment workflows. Depth inside a small number of complex accounts may create more value than shallow horizontal expansion.
What breaks the model?+
If renewal economics remain near CPI uplift, AI modules fail to earn budget owner sponsorship, and no logo diversification occurs inside 24-36 months, the asset remains a concentrated workflow tool and downside dominates the risk-adjusted case.
16 | Appendix
Supplemental detail on the themes that matter most to the investment case.
This appendix provides additional context on selected operating, commercial, and market themes referenced in the main memo. It is intended to give investors more detail without interrupting the primary narrative flow.
How to interpret the company's current revenue profile+
Garner should not be valued as a clean scaled SaaS asset today. The revenue base blends recurring workflow revenue, services, and implementation support. The underwriting distinction is that the recurring base provides durability, while services revenue gives implementation access but should receive a lower quality rating until it converts into repeatable productized work.
What would make AI monetization real rather than narrative?+
The economic case is not simply that AI can automate tasks. It is that a governed execution layer can reduce labor intensity, compress cycle time, and create measurable outcomes that can be priced against operating budgets rather than IT line items. The commercial test is whether AI modules reduce manual exception work and improve workflow throughput enough to support outcome-based pricing.
What evidence is needed that Garner can scale beyond bundled services?+
The current customer footprint proves operational relevance, but the valuation rerating requires evidence that Garner can sell repeatable modules without every deployment behaving like bespoke services. Productized workflows, standardized implementation playbooks, module-level pricing, and reusable UI patterns are the key markers that the asset is becoming software-led.
How to interpret the customer base appropriately+
The installed base is narrow but meaningful. Chevron and Exxon Mobil matter because they indicate the product can sit inside complex supermajor workflows, not because the company has already solved broad go-to-market. Seplat should be viewed as continuity evidence through asset ownership transition rather than a fully independent new-logo proof point.
What the expansion story really depends on+
Expansion depends first on renewal economics inside the anchor accounts, then on packaging that makes the solution easier to buy and deploy elsewhere. A broad outbound motion is less important than proving that Chevron and Exxon workflows can be converted into referenceable modules for adjacent supermajors, EPC channels, NOCs, and selected heavy-industry operators.
Frontier stack sequencing: what should be hardened first?+
Context and governance layers should be hardened before broad autonomy rollout. Systems-of-record integration, business context, role permissions, auditability, and exception history are the foundation. Agent execution should follow only where the company can prove bounded decisions, measurable outcomes, and clear human approval thresholds.
Cross-customer signal layer: where is the moat and where are the constraints?+
The attractive long-term idea is an anonymized benchmark layer across vendor risk, exception patterns, procurement friction, and resolution outcomes. The constraint is data ownership and customer confidentiality. The diligence question is not whether signal exists; it is whether Garner can convert signal into defensible intelligence while respecting customer-hosted boundaries and contract permissions.
Labor-budget framing: why pricing should move away from IT software logic+
Garner's pricing should eventually attach to avoided labor, reduced rework, faster resolution, and lower operating leakage. That moves the buyer conversation from software seat economics to operating-budget protection. The commercial proof point is a pricing amendment or module structure explicitly tied to measurable labor and throughput outcomes.
Contract conversion: what bridge terms matter most?+
Project-to-production transitions need explicit bridge terms at the design stage: renewal triggers, module pricing rights, data-use permissions, implementation scope limits, and evidence standards for outcome-based pricing. Without those terms, strong workflow usage can still behave like project revenue rather than durable recurring value.
What investors may want to diligence further+
Priority diligence areas include revenue classification, customer concentration, renewal terms, data rights, AI module evidence, implementation repeatability, key-person retention, gross margin by work type, product roadmap credibility, and whether customer-sponsored use cases can be packaged into repeatable commercial modules.
17 | Future Platform Architecture
From records to governed execution.
Garner's future-state architecture should make the investment thesis visible: the company is not merely adding AI to workflow software. It is layering interfaces, agents, measurement, domain intelligence, and governance over an operating context base that already sits across energy workflows.
Self-improvement loop
Governance
Enterprise Governance
Controls that span every layer so automation can scale inside high-consequence energy environments.
Audit TrailRole-Based PermissionsWorkflow ControlsHuman-in-the-Loop ApprovalsData SovereigntySOC 2
Interfaces
Interfaces
Role-specific surfaces for every operating persona, from field supervisor to procurement lead to executive sponsor.
Garner WorkspaceWorkflow CopilotOps DashboardsBusiness ApplicationsGarner Pilot
Workflow execution
Workflow Execution
Agents and workflow services that execute, automate, and coordinate energy operations at scale.
GarnerFlowGarnerDetectGarnerReviewGarnerAWPGarnerBidGarnerTextThird-Party Agents
Evaluation & optimization
Evaluation & Optimization
Every agent action measured so accuracy, overrides, resolution rates, and ROI evidence improve the system over time.
AccuracyOverridesResolution RatesROI TrackingTuning
Agent intelligence
Agent Intelligence
Energy-domain reasoning across AWP logic, vendor behavior, SOPs, geography-specific requirements, and customer-specific operating rules.
Q&ARoot CauseRecommendationsPrioritizationSOP LogicPredictive Models
Business context
Business Context
The moat: shared operational context built over years inside Chevron and Exxon Mobil, spanning data, systems, workflows, documents, communications, approvals, and exceptions.
DataSystemsWorkflowsDocumentsCommunicationsApprovalsExceptions
Systems of record
Systems of Record
Enterprise and supply-chain systems already connected across the operating network.
ERPProcurementMaintenanceFreightSupplier SystemsEmailDocsSpreadsheetsExternal Participants