Applied Intelligence. Engineered for the Real World.
ANHCRA designs, builds and deploys advanced AI systems for companies turning artificial intelligence into real products, workflows and operational capability.
The name is the long-term belief. AI understands language; we believe the next generation of systems will need to understand the human behind it — intent, context, history and behavior — and reason about more than an isolated prompt.
That research direction shapes how we engineer today: systems built around the humans they serve, with judgment, controls and evidence designed in from the start.
ANHCRA designs and implements production agent systems capable of reasoning across tasks, interacting with software, coordinating specialized agents, retaining operational state and executing workflows under defined controls.
07Agent EvaluationMeasure whether agents actually complete the task correctly.
Engineering capability, not vocabulary.
03 / Model Engineering & Fine-Tuning
Make the Model Fit the Problem.
ANHCRA works with organizations that have reached the limits of generic model behavior and need intelligence specialized around proprietary data, tasks, workflows or operating constraints.
01Custom Model Fine-TuningData preparation → baseline evaluation → SFT / LoRA / QLoRA → comparison → production deployment.
02Tool-Use Fine-TuningTrain models around structured actions, APIs and domain-specific tool use.
03Domain AdaptationSpecialize open models around industries, terminology, processes and proprietary knowledge.
04Preference & Post-TrainingImprove behavior around quality criteria instead of relying exclusively on prompt engineering.
05DistillationTransfer useful capabilities from expensive models into smaller specialist systems.
06Quantization & OptimizationReduce memory usage, latency and inference cost.
07Custom Small Language ModelsBuild narrow models for high-volume tasks where frontier-model economics do not make sense.
Sometimes the answer isn't a better prompt. It's a better model.
04 / Enterprise RAG & Architecture Systems
Build AI Around What Your Organization Actually Knows.
ANHCRA engineers retrieval systems for organizations whose knowledge lives across documents, databases, applications, policies, conversations and constantly changing internal sources.
We design the complete retrieval layer rather than merely attaching a vector database to an LLM.
01
Ingestion Architecture
Connect and normalize complex information sources.
02
Document Intelligence
Parse, classify and structure PDFs, contracts, records and other enterprise content.
03
Retrieval Architecture
Dense, sparse, hybrid and graph-based retrieval depending on the problem.
04
Reranking & Query Transformation
Improve what reaches the model before generation begins.
05
Access-Aware Retrieval
Respect user identity, roles and document permissions.
06
Citation & Evidence Systems
Connect generated answers back to source information.
07
Retrieval Evaluation
Measure recall, relevance, grounding and failure cases.
08
Freshness Pipelines
Keep knowledge synchronized as source systems change.
A RAG system is only useful when it retrieves the right information, for the right user, at the right time.
05 / AI Data, Evaluation & Model Quality
Build the Data That Makes AI Better.
ANHCRA builds the datasets, evaluation systems and quality infrastructure required to train, test and continuously improve production AI.
Golden set — labelled
01Training Data EngineeringCleaning, deduplication, transformation, taxonomy, difficult-example mining and training dataset construction.
02Synthetic DataGenerate controlled examples when real data is insufficient, private or missing important edge cases.
03Golden DatasetsCreate trusted scenarios used to compare every future version of an AI system.
04Custom BenchmarksBuild domain-specific benchmarks around actual business capability.
05Preference DataConstruct ranking and preference datasets for model adaptation.
06LLM-as-a-Judge SystemsDesign and calibrate automated evaluators.
07AI Regression TestingRun large evaluation suites before model, prompt, retrieval or agent changes enter production.
A specialist practice, not an afterthought.
06 / AI Reliability, Observability & Security
Production AI Needs More Than Accuracy.
ANHCRA engineers the systems required to understand how AI behaves after deployment — and to identify where it can fail before those failures become operational problems.
Trace prompts, models, retrieval, tools, agent trajectories and production failures.
prompts · tools · trajectories · failures
03 / ATTACK● ADVERSARIAL
Red Teaming
Actively attack AI systems through prompt injection, data extraction, tool abuse, malicious context and adversarial workflows.
injection · extraction · tool abuse
04 / POLICY● ENFORCED
Guardrails & Containment
Engineer controls around what models and agents are permitted to access, generate and execute.
access · generation · execution
Agent Regression Testing
Before a new version ships, it has to earn it.
Every candidate change — model, prompt, retrieval or agent logic — runs against the full scenario suite. Regressions on critical paths block the deployment automatically.
anhcra — regression run v2.4.1CANDIDATE
suite.scenarios0executed against golden set
eval.task_success0%vs production baseline ✓
eval.tool_error0%fewer tool failures than baseline ✓
eval.cost0%routing + caching improvements
eval.critical_paths0no critical regressions ✓
DEPLOYMENT APPROVED
07 / AI Infrastructure, Private AI & Optimization
Take AI From Prototype to Production.
This is where the painful engineering questions get answered — the ones companies encounter after something works in a notebook.
01AI Production ArchitectureDesign infrastructure around models, retrieval systems, agents and workloads.
02Private Enterprise AIDeploy models and retrieval systems inside controlled enterprise environments.
03Model ServingProductionize open-weight and specialized models.
04Inference OptimizationImprove latency, throughput, GPU utilization, batching and caching.
05Intelligent Model RoutingUse different models based on request complexity, workload and economics.
07AI Cost OptimizationAnalyze complete AI workloads and redesign them around cost-performance efficiency.
Your most expensive model shouldn't answer your easiest questions.
Intelligent routing sends each request to the smallest system that can handle it — and escalates only when the problem earns it.
FIG. 02 — INTELLIGENT MODEL ROUTING
08 / Enterprise AI & Intelligent Workflows
Turn Business Processes Into Intelligent Systems.
ANHCRA works with organizations to identify processes where AI can understand information, make controlled decisions, operate software and perform meaningful portions of work.
01
Customer Operations
AI customer supportVoice agentsCustomer-success workflowsTicket resolutionArchitecture assistants
02
Sales & Revenue
AI SDR systemsLead qualificationCRM automationSales intelligenceResearch agentsProposal workflows
Every technology we built taught us something about the next one.
Before ANHCRA became our next chapter in artificial intelligence, our journey moved through consumer technology, global software businesses, startup infrastructure, intelligent mobility and AI for education. Different products. Different industries. Different problems. But one continuing idea:
Build technology that becomes useful in the real world.
PRODUCTS → COMPANIES → ECOSYSTEMS → INTELLIGENCE
SAMPARK.ME
Reachable without exposing your information01 / 05
One simple idea — making people reachable without exposing their information — grown into a product used by more than a million people.
More than a million people worldwide use it.
It reached a national stage on Shark Tank India, and runs with PVR Cinemas as a channel partner and IndianOil as a sponsor partner.
02 / YNAPS
From a product to building companies.
A Spain-based global technology business, conceiving, engineering and operating products again and again.
Eight brands sit in the portfolio: Nodly’s, BuyWWS, NGF132, Peklenc Research, Trustyfire, Page—Server, Aaviface and Enterployee.
One product became the pattern for building the next, and the next.
03 / PEKBUS
When will it reach me?
An Uber-like fleet experience for schools and industries — live movement, stop-specific ETA, calmer mornings.
It answers four things: where the bus is, when it reaches your stop, when you need to leave, and the complete journey.
Built for schools and industries, where the same route runs every morning.
04 / AI FOR EDUCATION
Taking a teacher beyond the classroom.
An AI assistant for teachers in rural India — extending a teacher's support to students even when the teacher isn't there.
The teacher stays human. The AI avatar is always available. The students are many, and anywhere.
It covers homework, questions, revision, explanation and learning support — one teacher, more availability, more students supported.
05 / BUENSTART
Helping other founders build theirs.
A startup accelerator — with ANHCRA as its permanent AI panel member, building the intelligence inside new companies.
The founder journey runs from startup idea and product through AI strategy, model architecture, RAG and data, agents, infrastructure, evaluation and production.
Having built its own companies, ANHCRA now builds the intelligence inside other people’s.
Intelligence is changing what companies can build.
What they can automate.
What they can understand.
What they can become.
The interesting question is no longer:
What can AI do?
What can we build with it?
Every company has its own data. Its own systems. Its own workflows. Its own problems. Its own opportunities.The intelligence built around them should be just as specific.
Tell us what you are building and where it is getting stuck. The problem determines the architecture — so the more concrete you can be, the more useful our first reply will be.
Studio
1243 Dw We Work Futura, Magarpatta Rd, Hadapsar, Pune, Maharashtra 411028
