Pre-launch · Chicago, IL

Make sense of what's complex. Measure it with clarity and rigor.

Cerndaia helps small and mid-sized organizations adopt AI well, then turns that use into numbers you can show to buyers, investors, and regulators.

The Cerndaia mark: a violet ring around a two-tone green and grey eye
The gap

Two pressures, one desk

Every organization knows it needs to use AI, and use it well. The hard part isn't awareness — it's that doing it well gets complicated fast, and the impact is easy to leave unmeasured. At the same time, larger buyers and investors increasingly ask for ESG data as a condition of doing business.

The advisory market has filled with generalists who hand over a list of prompts and disappear, and with large firms priced for enterprise budgets. A separate, crowded market has formed around using AI to produce ESG reports. What's genuinely rare is the inverse: treating an organization's own AI usage as an ESG input, and measuring it. That's the white space Cerndaia occupies.

Why now. Responsible-technology frameworks have moved from optional to expected. An international, certifiable standard for responsible AI management already exists and is being adopted by the largest technology companies, so buyers now recognize and ask for this language. A small, specialized firm can serve the businesses the standards bodies and large firms overlook.
How it works

One engagement, three moves

Each build runs in this order — diagnose, then equip, then measure — because the measurement only means something once the first two are real.

01 · Enable

Diagnose & design

Study the business, interview the team, map workflows, and rank where a tool helps most by impact and ease.

02 · Equip

Build & train

A custom prompt library for the top workflows, a recommended tool stack, and live training on the tools that actually fit.

03 · Measure

Translate to ESG

Turn usage into ESG language: cost and efficiency gains, an environmental footprint estimate, and workforce impact.

A monthly retainer wraps around all three — monitoring usage, re-optimizing, moving the team to better tools as they appear, and refreshing the measurement every quarter.

The framework

Usage becomes measurable impact

The signature product: your organization's own AI usage, read as an ESG input.

AEMF v1.0 · stress-tested across a 30-organization casebook
Usage inputs
Token / compute volume
Tool & subscription spend
Workflows automated
Hours & headcount effect
Cerndaia
model
in →→ out
Measured outputs
E · Environmentalcompute / footprint estimate
S · Socialworkforce & reskilling impact
G · Governanceresponsible-use policy & controls

A note on the environmental claim: the chain from lower token use to lower compute to lower footprint is real but small and hard to measure precisely at one company. Cost-efficiency and workforce impact lead; the carbon figure is presented as a clearly labeled directional estimate, never as an audited number.

Who it's for

Built for teams that have to prove the work

ESG-pressured brands

Consumer goods, food and beverage, and manufacturers or suppliers selling to large retailers or courting investors — facing real pressure to report sustainability data.

Professional services

Accounting, legal, marketing, and consulting practices that run on documents and knowledge work, where returns are fast and obvious.

Mission-driven organizations

Impact-oriented teams and funds that want their tool adoption to reflect the same values as their mission.

Why Cerndaia

Discernment before delivery

It studies first

The work begins by studying the specific business, not by handing over a generic template.

It stays

The retainer monitors, re-optimizes, and moves the client to better tools as the landscape shifts.

It proves the value

No other small firm turns a company's own tool usage into a measurable report for buyers and investors.

It's personal

The founder does the work directly, not a rotating cast of junior associates.

Who's behind it

Built by one person, in the room the whole time

Sahithi Salikineedi

Cerndaia is built and run by Sahithi, working at the intersection the firm is built on — applied AI, measurement, and governance.

She holds a Master of Public Policy from the University of Chicago's Harris School of Public Policy, with graduate coursework spanning AI ethics and governance, tech law and policy, econometrics and causal inference, applied statistics, and ESG analytics for investing. Her undergraduate degree, a First Class BSc (Honours) in Economics, was completed ranked first nationally among entrance-test candidates.

She works inside the tools she recommends — prompt design, tool selection, workflow automation — backed by Python, R, and SQL. Every engagement starts with studying the business, and is worked directly, start to finish. Based in Chicago.

Founder photo pending — send one and it goes here, beside the bio.
Get in touch

Cerndaia is pre-launch. Early conversations start now.

Paid engagements begin once work authorization is active. Until then, tell us what your team is running into, or ask to be first in line when Cerndaia opens — we reply to every note.