It could do the reading for you.
Assistants, agents and retrieval systems that read, sort and draft, so your people decide instead of dig.
- 3 risks found
- Auto-renews, 60-day notice
- Liability capped at fees
- Data kept for 7 years
Assistants, agents and retrieval systems that read, sort and draft, so your people decide instead of dig.
A working first version in weeks, on a foundation you won’t have to throw away when it takes off.
Storefronts, platforms and internal tools that look like you and still work at two in the morning.
Audits, penetration tests and secure-by-design architecture, led by a Certified Ethical Hacker.
Rejected · tampered
Pipelines, models and dashboards that turn what you already collect into what happens next.
Smart contracts and ledgers for records that have to be trusted by people who don’t trust each other.
[ Selected work ]
Everything below is real: captures, code and marks from things we’ve built.





# pip install inscrape from inscrape import Inscrape client = Inscrape("sk_your_token_here") # Scrape any URL result = client.scrape("https://example.com") print(result.content) # Get Markdown md = client.markdown("https://example.com")

$ npm i -g @gkganesh12/codecraft-cli $ codecraft init $ codecraft › /plan scope the change › /code write inside the guard › /verify check it against the rules

$ brew install gkganesh12/tap/gk-stack $ gk-stack init $ claude -p "/ship" Tests 1 failed | 4579 passed › Stopping here. I won’t commit or push broken code.

# POST /api/v1/documents
{
"evaluator": "citation_existence",
"severity": "CRITICAL",
"confidence": 0.95,
"explanation": "Citation '123 F.3d 456
(9th Cir. 2019)' does not match any
opinion in CourtListener."
}


you scan 10.10.10.5 and find vulnerabilities
agent runs nmap -sV -sC
→ finds Apache 2.4.49
→ looks up CVE-2021-41773 (CVSS 9.8)
→ stores finding in knowledge graph

from model_train import PrivacyPreservingCTGAN # CTGAN trained with DP-SGD (Opacus) model = PrivacyPreservingCTGAN( use_dp=True, epsilon=1.0, delta=1e-5 ) metrics = model.train(df) print(metrics["epsilon"]) # privacy spent
The Uncovering · studio still-life series
[ How we build ]
Move your cursor. The lens shows what’s running behind each screen. We design the part you see and engineer the part you don’t.
Underneath: products, stock, orders and accounts modelled so nothing gets lost between the cart and the courier.

model Product {
id String @id
name String
slug String @unique
priceInr Int
mrpInr Int?
category String
occasions String
featured Boolean
stock Int?
orderItems OrderItem[]
reviews Review[]
}
Underneath: two engines, retrieval and heuristics, mapping every conversation to a competency framework.

Underneath: every record is signed, canonicalised and checked. A tampered document is rejected, on screen, in real time.

def verify_agent_facts(doc, key):
proof = doc.get("proof")
if proof["verificationKey"] != key:
raise VerificationError(…)
body = copy.deepcopy(doc)
body.pop("proof", None)
try:
VerifyKey(pub).verify(
_digest(body), sig)
except BadSignatureError:
raise VerificationError(…)
[ What we bring ]

[ What we believe ]
Most studios are good at one. You need both in the same room, arguing early, so the thing that looks right also works right. That’s the whole studio.
One last thing, about the name.
a·le·thei·a / ἀλήθεια /
noun, Greek. Truth. Literally “un-hidden”: the state of a thing when nothing about it is concealed.
It’s how we work. You see what we’re building, what it costs and what’s left, every week, without having to ask.