OldKnowledge,New Vessel.
Essays on on-device AI, data sovereignty, and building systems that keep knowledge where it belongs.
Enter the archive →— 00 / ThesisEvery business runs on knowledge older than its software.
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AI for Materials and Molecules in 2026: A Predicted Material Is a Hypothesis With a Price Tag, So Build the Stack Around the Cost of a False Positive, Not the Count of Candidates
Scale-Up vs Scale-Out in 2026: The Interconnect Sets the Size of Your Machine, So Size the Domain to the Collective and Buy the Fabric by Its Exit Cost, Not Its Bandwidth Number
Confidential Databases: Encryption in Use Is a Query-Shape Decision, So Choose the Boundary by Which Operator Must Run Blind, Not by the Word "Confidential" (2026)
Multi-Robot Traffic Management: The Intersection Belongs to One Authority, So Standardise the Robot Interface and Never Let Two Fleet Managers Share a Corridor (2026)
Digital Twin Data Models and Ontologies: The Ontology Is the Twin, So Choose It by Who Must Read the Twin From Outside, Not by the Platform You Run (2026)
अथ प्रथमोऽध्यायः ॥
विद्या ददाति विनयं विनयाद् याति पात्रताम् ।
पात्रत्वाद्धनमाप्नोति धनाद्धर्मं ततः सुखम् ॥
We digitize centuries-old manuscripts. Then we build with the same discipline.
AppScale's roots are in a quiet project: structuring classical Sanskrit texts into faithful digital form. Extraction, structure, provenance, sovereignty — the same principles now power our client work.
Built for Every Business
Intelligence that never leaves the device
Offline-first, data-sovereign systems — LLMs, vector search, inference at the edge.
02Document IntelligenceAir-gapped document vaults
Sealed, searchable, provable.
03AI ProductsFull-cycle AI product builds
Mobile-first, production-grade.
04MCP & AI SecuritySecuring the agentic stack
Tool poisoning, prompt injection, confused deputies — studied and hardened.
05Indic Language AIOCR for scripts the world forgot
Sovereign OCR for Indic scripts.
06Consulting & Architecture19+ years shipping at scale
OTT, e-commerce & mobility platforms serving millions.
AI for Materials and Molecules in 2026: A Predicted Material Is a Hypothesis With a Price Tag, So Build the Stack Around the Cost of a False Positive, Not the Count of Candidates
AI materials discovery in 2026: UMA, Orb-v3, MatterGen, self-driving labs and Microsoft Discovery GA, compared by cost per candidate and false-positive mode, with four gates.
Scale-Up vs Scale-Out in 2026: The Interconnect Sets the Size of Your Machine, So Size the Domain to the Collective and Buy the Fabric by Its Exit Cost, Not Its Bandwidth Number
NVLink 6 vs UALink over Ethernet vs Ultra Ethernet 1.1 vs co-packaged optics in 2026: size the scale-up domain to your model's collectives and buy the fabric by exit cost.
Confidential Databases: Encryption in Use Is a Query-Shape Decision, So Choose the Boundary by Which Operator Must Run Blind, Not by the Word "Confidential" (2026)
Confidential databases in 2026: Always Encrypted enclaves vs MongoDB Queryable Encryption vs confidential VMs, compared by which operators survive and who is excluded.
Multi-Robot Traffic Management: The Intersection Belongs to One Authority, So Standardise the Robot Interface and Never Let Two Fleet Managers Share a Corridor (2026)
Why multi-vendor AMR fleets deadlock, what VDA 5050 3.0 (March 2026) standardises and leaves out, and the single-traffic-authority architecture that owns the intersection.
Digital Twin Data Models and Ontologies: The Ontology Is the Twin, So Choose It by Who Must Read the Twin From Outside, Not by the Platform You Run (2026)
How to choose a digital twin data model in 2026: DTDL vs NGSI-LD vs Asset Administration Shell vs Brick, the two-layer canonical model, and the 2027 battery passport deadline.
FP4 Inference in Production: The Fourth Bit Lives in the Scale, So Choose the Block Format and the Kernel Before You Choose the Model (2026)
FP4 inference in 2026: how NVFP4 and MXFP4 differ in block scale, why the 2x throughput needs Blackwell, the Hopper W4A16 fallback, and a per-workload adoption path.
Modelling the ROI of a Digital Twin: A Twin Has No ROI, Decisions Do, So Price the Decision It Changes Before You Price the Twin (2026)
Digital twin ROI in 2026: model value per decision the twin changes, against a measured baseline, with a worked payback example and the costs that hide.
Right to Erasure in Vector Stores: Delete Is a Request, Erasure Is a Proof, So Design the Purge Path Before the First Embedding (2026)
GDPR erasure in RAG systems: why a vector delete only tombstones data, and the lineage, ledger, compaction and backup design that proves it is gone in 2026.
Designing for the DMA: Interoperability Is an API Product With a Regulator in the Room, So Build the Access Layer Once (2026)
DMA interoperability in 2026: one access layer for identity, consent, scoped tokens, integrity rules and audit, plus how third parties design for slow access.
Continual Learning in Production: A Model That Keeps Learning Is a Release Train, So Gate Every Update Like a Deploy (2026)
Continual learning in 2026: every model update is a release. Gate it on a frozen memory set, use replay against catastrophic forgetting, keep a rollback.
Sim-to-Real Transfer Architecture: The Reality Gap Is a Measurement, Not a Feeling, So Budget It Before You Randomise It (2026)
Sim-to-real transfer in 2026: the reality gap is a measurement, not a feeling. Decompose it, calibrate what you can, randomise the rest, gate on hardware.
Continuous Profiling in Production: The Profile Is the Only Telemetry Denominated in Money, So Run It as a Cost Ledger First and a Debugger Second (2026)
Continuous profiling in 2026: profiles are the only telemetry denominated in money. Run eBPF sampling as a fleet cost ledger first, a debugger second.
Terraform at Platform Scale: State Is the Unit of Blast Radius, So Split It by Who Changes What and How Often, Not by Environment (2026)
How to structure Terraform for many teams in 2026: state is the unit of blast radius, so layer it by owner and change cadence, then pick Stacks or Terragrunt.
Islands Architecture and Partial Hydration in 2026: Hydration Is a Per-Component Tax, So Your Interactivity Ratio Picks the Architecture, Not the Framework
Islands vs React Server Components vs Qwik in 2026: hydration is a per-component tax, so measure your interactivity ratio before you pick an architecture.
Secure Multi-Party Computation for Cross-Organisation Analytics: The Protocol Is the Easy Part, the Non-Collusion Contract Is the Product (2026)
Secure multi-party computation in production in 2026: why non-collusion governance matters more than the protocol, how to architect it and when to pick a cheaper tool.
Safety Certification for AI-Driven Robots: Certify the Envelope, Not the Policy, and Keep Learning Out of the Safety Function (2026)
How to certify an AI-driven robot under the EU Machinery Regulation in 2026: keep machine learning out of the safety function and certify a deterministic envelope.
Platform Team Funding and Staffing: Chargeback Taxes Adoption, So Fund the Floor, Meter the Variable and Never Bill the Paved Road (2026)
How to fund and staff a platform team in 2026: why chargeback taxes adoption, the fund-the-floor hybrid model, bottom-up headcount and what to report to finance.
Robot Teleoperation Fallback Architecture: The Remote Human Should Advise, Not Drive, and the Operator Ratio Is Your Real Business Model (2026)
Robot teleoperation fallback done right: the robot owns safety, remote operators advise rather than drive, and the operator ratio is your real business model.
Differential Privacy in Production, 2026: Epsilon Is a Budget, Not a Setting, and Deployments Fail at the Ledger, Not the Math (2026)
Differential privacy in production fails at the ledger, not the math. How to budget epsilon per dataset, gate queries, use NIST SP 800-226, and when to skip DP.
AI Weather Models in Production, 2026: The Speedup Is an Ensemble Dividend, and You Only Collect It If Your Decisions Consume Probabilities (2026)
AI weather models like ECMWF AIFS and WeatherNext 3 made ensembles cheap. Why the value is in calibrated probabilities, the pipeline, and when not to switch.
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