Technoscore

TechnoScore reports:

• ISO certification
• 200+ expert IT professionals
• 400+ global clients
• 1,400+ noteworthy projects
• 6,000+ projects delivered
• 98% client retention
• Experience serving clients across more than 45 countries

The company's mission follows the 5 Ds: Discover, Define, Design, Develop, and Deliver. Its stated values include transparency, excellence, genuineness, and dedication.

Offices

• India: Floor 3, Vardhman Times Plaza, Plot 13, DDA Community Centre, Road 44, Pitampura, New Delhi - 110 034, India
• USA: 1968 S. Coast Hwy #499, Laguna Beach, CA 92651
• UK: 86-90 Paul Street, London, EC2A 4NE

TechnoScore is described as the Digital Engineering Services Division of SunTec India.

Application Development

• Web applications using React, Next.js, Node.js, Python, PostgreSQL, and TypeScript
• Mobile applications for iOS, Android, Flutter, and React Native
• SaaS products with multi-tenant architecture, billing, SSO, role-based access control, audit trails, and feature flags
• Technical architecture, testing, CI/CD, documentation, and production delivery

Data Services

• Data engineering using Snowflake, BigQuery, Databricks, dbt, Airflow, Kafka, and Flink
• Data annotation for image, video, text, and audio, including specialized domain data
• Data processing, enrichment, normalization, validation, deduplication, and integrity checks

Cloud and DevOps

• Cloud architecture, landing zones, workload migration, and multi-cloud strategies for AWS, Azure, and Google Cloud
• DevOps and CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, and ArgoCD
• Progressive delivery, secrets management, automated rollback, cost visibility, rightsizing, and cloud cost optimization

QA and Testing

• Test automation using Selenium, Playwright, Cypress, and Appium
• API and contract testing
• Load, stress, soak, and spike testing
• Security testing, penetration testing, SAST, DAST, IAST, dependency analysis, threat modeling, and secure code review

Modernization and Staffing

TechnoScore supports application modernization, cloud migration, platform re-engineering, security and compliance modernization, and legacy application transformation. It also provides pre-vetted developers and AI developers across front-end, back-end, full-stack, mobile, DevOps, cloud, data engineering, QA, MLOps, NLP, computer vision, and AI agent development.

Agent services include:

• Workflow discovery, agent architecture, prompt orchestration, tool calling, and function calling
• Integration with APIs, databases, code execution environments, browsers, files, CRMs, ERPs, ticketing systems, document repositories, and SaaS tools
• Short-term memory, long-term vector storage, and structured state persistence
• Guardrails, confidence thresholds, fallback logic, retries, and exception handling
• Human approval gates and escalation paths
• Evaluation harnesses, regression tests, task-completion scoring, latency benchmarks, and tool-use accuracy checks
• Audit logging, observability dashboards, cost monitoring, versioning, and rollback

Single- and Multi-Agent Systems

Single-agent systems can use API connectors, database queries, browser use, code execution, file I/O, memory architectures, and human-in-the-loop controls.

Multi-agent systems can use orchestrator-worker patterns, specialized agents, structured message passing, shared state, task routing, queue prioritization, and agent-level failure containment.

Delivery Process

1. Workflow audit and scoping: Map the target workflow, dependencies, failure modes, success metrics, and evaluation criteria.
2. Evaluation harness and tool build: Establish performance benchmarks and develop connectors against real APIs.
3. Agent build and integration: Add agent logic, memory, error handling, and escalation paths, followed by shadow-mode testing.
4. Production rollout and monitoring: Use phased traffic rollout with monitoring for cost, latency, task completion, and other agreed metrics.

TechnoScore offers a two-week workflow audit that produces an agent specification and realistic performance estimates. The website states that its approach targets production delivery in 6–10 weeks for the comparison shown.

Generative AI

Services include:

• LLM integration, RAG pipelines, and fine-tuning
• Prompt engineering and evaluation frameworks
• Latency and cost optimization
• Production fallback handling and observability

Clearly scoped MVPs, pilots, or first production releases are described as typically taking 6–10 weeks.

NLP and Chatbots

TechnoScore develops domain-adapted NLP models for intent recognition, entity extraction, classification, and sentiment analysis. Conversational AI systems can be integrated with support stacks and support multilingual and multi-domain use cases. The website describes 6–8 week delivery to production for these services.

Machine Learning

Machine learning services cover supervised and unsupervised model development, classification, prediction, forecasting, recommendation systems, anomaly detection, and computer vision. Engagements can include data preparation, feature engineering, model training, validation, deployment, monitoring, and retraining workflows.

Production Baseline

AI and ML engagements include:

• Evaluation frameworks, benchmarks, test sets, and success metrics
• Agreed production latency targets
• Failure-mode and hallucination-risk mapping for relevant systems
• Human-in-the-loop escalation and override mechanisms
• Token, compute, and per-request cost modeling
• Privacy-safe logging, access controls, retention rules, dashboards, and error alerting
• Team training on prompting, evaluation, and model management

The technology stack includes Python, R, JavaScript, TypeScript, Java, TensorFlow, PyTorch, scikit-learn, XGBoost, LightGBM, OpenAI, Anthropic Claude, Google Gemini, Meta Llama, Mistral, LangChain, LlamaIndex, Haystack, and multiple vector databases and MLOps platforms.