The opportunity that was never real.
A promising use case that cannot produce enough value to justify the cost.
THE PROBLEM
Most AI waste begins before anything gets built.
Companies invest in the wrong use case, launch without a path to adoption, or buy tools their teams cannot use. By the time the mistake becomes obvious, the budget and momentum are already gone.
The pilot with nowhere to go.
An impressive demo without the data, ownership, or workflow needed for production.
The product nobody trusts.
A feature users try once, get burned by, and quietly stop using.
The tooling nobody adopts.
Licenses purchased across the company. Very few people using them meaningfully.
These are not model failures. They are decisions that should have been tested before the investment was made.We help companies make those decisions with evidence.
THE APPROACH
We find where AI pays before you spend.
We map how the work actually happens, test each opportunity against value, feasibility, and risk, then give you a prioritized plan — including what not to build.
BUILD THE CASE
WAIT FOR EVIDENCE
DO NOT BUILD
Map the real operation
We trace how work, data, and decisions actually move — not how the org chart says they do.
Test value against reality
Each opportunity is scored against business value, feasibility, adoption, and risk.
Make the call plainly
You get a prioritized pursue, defer, and skip list — with the evidence behind every decision.
OUR SERVICES
SERVICE 01
AI Opportunity Advisory
"Where will AI create measurable advantage?"A ranked investment thesis grounded in workflow economics, data readiness, operating constraints, and execution risk.
SERVICE 02
AI Product Validation
"Is this product worth building with AI?"Evidence on demand, technical viability, unit economics, and trust requirements before you commit product resources.
SERVICE 03
Enterprise AI Strategy
"How should AI reshape the operating model?"A sequenced portfolio across build, buy, and enablement — prioritized by value, dependencies, and execution risk.
SERVICE 04
Team Enhancement
"Can our people use AI more effectively?"We train your people to use AI better in their day-to-day work, with practical guidance tailored to their roles and workflows.
OPPORTUNITY PORTFOLIOSAMPLE OUTPUT
Value against effort
RANKED BY ECONOMIC AND OPERATIONAL EVIDENCE
VALUE ↑EFFORT →
01
03
02
04
PRODUCT EVIDENCE GATESAMPLE CASE
Build confidence
EVIDENCE BEFORE PRODUCT COMMITMENT
USER DEMAND84
VIABILITY76
ECONOMICS68
TRUST RISK31
RECOMMENDATIONPROCEED TO PILOT
EXECUTION SEQUENCE12-MONTH VIEW
From portfolio to sequence
DEPENDENCIES BEFORE ROADMAP THEATER
NOW
Workflow intelligenceData foundationsNEXT
Decision supportProduct pilotsLATER
AutomationPlatform scaleOPERATING CAPABILITYOWNERSHIP TRANSFER
Build the system around the tools
SKILLS, WORKFLOWS, AND GOVERNANCE
EXECUTIVESOPERATORSBUILDERS
OWN
WORKFLOWSEVALUATIONGOVERNANCE
EXPERIMENTOPERATE
PREMIUM — CUSTOM DELIVERY
Custom AI Software & Tools
When off-the-shelf software cannot support the workflow, we design and build the system for you — focused SaaS products, internal tools, automations, and AI-enabled operating software.
Talk to us about what you need built ↗DELIVERY SYSTEMsample
Workflow specificationCOMPLETE
Product architectureCOMPLETE
Production buildIN PROGRESS
DELIVERY PROGRESS72%
PREMIUM — TECHNICAL TEAMS
AI Evaluation & Reliability
For teams with live LLM systems who need to know their AI actually works in production. Evaluation pipelines, reliability audits, regression coverage — engineering, not vibes.
Talk to us about your eval stack ↗EVAL MONITORsample
487 ms p95
Eval pass rate98.2%
Regressions (24h)0
Coverage1,284 cases
THE FOUNDER
Built in systems wherebeing wrong is expensive.
Deepfield is led by Sriharsha Kanumilli, an AI and systems engineer who has worked on production programs spanning autonomous vehicles, global connectivity, conversational AI, and advanced aerospace. The common thread is not an industry. It is the discipline required to move from an impressive demonstration to a system people can trust.
The advice comes from having shipped the work, not from observing it at a distance.SRIHARSHA KANUMILLI · FOUNDER & PRINCIPAL
SELECTED SYSTEMS EXPERIENCE
Full Self-Driving
Production autonomy in a safety-critical environment, where reliability must survive the physical world.
Starlink
Systems operating at global scale across demanding infrastructure, hardware, and operational constraints.
Conversational AI
Customer-facing language systems designed for real usage, measurable quality, and continuous evaluation.
Advanced Aerospace
Engineering work in a high-consequence environment shaped by rigorous reliability, security, and operational requirements.
Every engagement gets that operating judgment directly. No junior handoff. No recycled transformation playbook.
FOUNDER-LED
BY DESIGN
BY DESIGN
GROUNDTRUTH LABS
Agent eval research coming soon.
Field notes on how AI agents actually perform in production — evals, reliability, failure modes. Published in the open. Research arm, not a sales channel.
STATUS
No field notes yet.
We're building eval tooling and running agent experiments in live systems. When there's something worth publishing, it lands here first.
HOW IT WORKS
Bounded scope. Clear deliverable. No retainer creep.
A call
Thirty minutes on how your business runs and where it hurts. No pitch.
An assessment
We map your operations against what AI can actually do today — fixed scope, fixed timeline.
A roadmap
Where AI pays, what to skip, who needs training. Yours to act on — with or without us.
Start with a call.
Thirty minutes on how your business runs and where AI actually fits. No pitch.
Book a call →founder-led · fixed scope · no retainer creep