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We design AI agents that automatically research, collect, validate, organize and report business data — helping companies save time, reduce manual work and grow faster.
Each agent is purpose-built for a specific business function. They can operate independently or as part of a coordinated multi-agent pipeline overseen by a central coordinator.
Autonomously scans websites, company directories, public LinkedIn pages and marketplaces to identify potential business contacts. Collects company names, decision-maker positions, email addresses, phone numbers and social profiles. Verifies contact data before adding it to the list.
Business benefits
Typical use cases
Crawls a website page by page, analyzing title tags, meta descriptions, H1–H6 heading structure, image alt text, internal link health, page speed signals, schema markup and keyword coverage. Produces a prioritized list of issues ranked by impact.
Business benefits
Typical use cases
Monitors product listings, seller profiles, price movements, review trends and category rankings on platforms like Amazon, eBay, Etsy and similar. Identifies market gaps, competitor price changes and contact data for suppliers and partners.
Business benefits
Typical use cases
Ingests raw data exports — spreadsheets, CRM dumps, CSV files from multiple sources — and applies rule-based and AI-driven validation to standardize formats, correct errors, fill in missing fields and separate clean records from those requiring review.
Business benefits
Typical use cases
Compares incoming records against existing databases using exact, fuzzy and phonetic similarity matching to flag duplicates by email, phone number, company name or address — even when data is inconsistently formatted.
Business benefits
Typical use cases
Manages the full lifecycle of contacts and deals in the CRM. Creates new records, updates statuses, logs communication history, assigns follow-up dates and moves leads through pipeline stages according to defined rules — without manual data entry by the team.
Business benefits
Typical use cases
Prepares every campaign element before any message is sent. Segments contacts into logical groups, creates personalized message templates from real data, assigns campaign metadata and batch IDs, and flags records for human review.
Business benefits
Typical use cases
Aggregates data from pipelines, CRM and operations tools, generating structured reports on a daily, weekly or custom basis. Covers processed records, leads generated, duplicates detected, campaigns prepared, conversion rates and overall pipeline health.
Business benefits
Typical use cases
Checks data collection, storage and processing activities against defined rules before any pipeline action runs. Verifies that data sources are permitted, limits are respected, required consent fields are present and mandatory checkpoints have been completed.
Business benefits
Typical use cases
Acts as the coordinator of a multi-agent system. Monitors the status of all running agents, validates results before handing them to the next stage, handles error conditions automatically, decides whether a result meets quality thresholds and escalates to a human operator when confidence falls below an acceptable level.
Business benefits
Typical use cases
Handles incoming customer questions, support tickets, FAQs, order updates, meeting requests and basic troubleshooting across email, chat and website channels.
Business benefits
Typical use cases
Tracks leads after first contact, sends follow-up messages, reminds teams when prospects go quiet and helps move opportunities through the sales pipeline.
Business benefits
Typical use cases
We use proven open-source and commercial AI infrastructure — without lock-in to a single provider.
We map existing workflows and identify the specific tasks where automation delivers the greatest return — starting with repetitive, high-volume, rule-based work.
We design the agent's logic, define boundaries for tool use and data access, build safeguards and establish human approval points where needed.
We create and integrate the agent using the right combination of LLM models, RAG pipelines, vector stores and custom knowledge bases for your context.
We deploy in your environment, connect with existing tools, monitor performance in production and iterate based on real-world results.
Tell us what you want to automate, and we'll design an agent system tailored to your workflow.
Build Your AI Agent