Results for “bot”

Create, review, debug, test, or reproduce Python Jupyter notebooks by inspecting format, executing cells top-to-bottom in a clean kernel, and verifying outputs.

Builds operational monitoring dashboards for Grafana, SigNoz, and similar platforms, focusing on answering operator questions about health, bottlenecks, and changes rather than displaying every metric.

Manage AWS S3 buckets and objects: create buckets, upload/download files, configure lifecycle policies, set up static websites, manage permissions, and implement cross-region replication.

Build table storage applications using the Azure Tables SDK for Java, supporting both Azure Table Storage and Cosmos DB Table API for NoSQL key-value data.

Compute TAM/SAM/SOM with top-down and bottoms-up methods, plan survey sample sizes with per-segment minimums, and score candidate segments against Kotler's five criteria.

Analyze PyTorch profiler and vLLM trace files with Perfetto SQL evidence. Use when working with torch profiler traces, merged_trace files, vLLM profiling logs, Perfetto trace analysis, GPU kernel hotspots, synchronization waits, rank imbalance, prefill/decode bottlenecks, or optimization reports.

Prevents silent decimal mismatch bugs across EVM chains by querying token decimals at runtime, caching by chain and token address, and using safe normalization for bots, dashboards, and DeFi tools.

Apply bottom-up and top-down role mining techniques to discover optimal RBAC roles from existing user-permission assignments, reducing role explosion and enforcing least privilege.

Evaluates the trade-off between file size reduction and image fidelity when encoding radio astronomy data using JPEG2000, benchmarking both lossless and lossy compression modes to determine the compression ratio at which visual artifacts first appear.

Generates integration test cases for .NET data access artifacts during Oracle-to-PostgreSQL database migrations, producing DB-agnostic xUnit tests with deterministic seed data that validate behavior consistency across both database systems.

Access blockchain RPC endpoints via Quicknode to read onchain data including balances, token prices, transaction status, gas estimates, and block data across Base, Ethereum, Polygon, Solana, and Unichain. Supports both API key and x402 wallet-based pay-per-request access.

Document end-to-end business processes in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being worked, and quantify the gap between processing time and total elapsed time.

Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.

Import raw data (CSV, XLSX, TXT, or MATLAB tables) into formats used by Sensor Fusion and Tracking Toolbox. Handles both ground truth trajectories and sensor detection data. For truth: builds trackingScenarioRecording, tuning timetable, truthlog, or converted table. For sensor data: builds task-oriented dataFormat structs (preferred) or objectDetection arrays (legacy). Use when importing flight logs, GPS logs, radar detections, IR measurements, lidar/camera bounding boxes, ADS-B data, AIS ship tracks, or any recorded data for use with trackers, filter tuning, or tracker evaluation.

Turn a customer's stated goals into a success plan that predicts the renewal. It sets time-to-value milestones, names an owner on both sides for each, and picks the leading indicators that tell you a year early whether this account renews. Built for B2B customer success teams, customizable to your CRM and product analytics. Trigger on "build a success plan", "onboarding plan for this account", "what are the milestones", "how do I know they'll renew", "time-to-value plan", or any post-sale planning.

Your data-fill agent. Connect a contact-enrichment tool (contact-level) or a company-enrichment tool (company-level), or both for the full waterfall, to fill gaps on any list. Given a name plus a company, find email, phone, LinkedIn, and title. Given a domain, find headcount, funding, technographic profile, and hiring intent. Trigger on "enrich these contacts with emails", "find LinkedIn URLs for {list}", "get phone numbers for {contacts}", "who are the decision makers at {company}", "complete this prospect list", "enrich this CSV", "get the technographic stack for {company}", "fill in missing data on {list}", or any data-completion, list-enrichment, or contact-lookup question.