Custom AI Software & Agent Factory

Ingests user behavior from web tracking, product analytics, email engagement, firmographic data (Clearbit), and intent signals (Bombora). An ML model dynamically updates lead scores in real time, auto-enriches records, matches leads to enterprise accounts using custom territories, and routes them via round-robin to specialized account executives while generating custom Slack briefing dossiers.

Automatically works out which incoming leads are most likely to actually buy, and sends each one straight to the right salesperson with a briefing — instead of someone sorting them by hand.

Pulls metadata from CRM deal terms into a contract generation engine. An LLM scans redlined vendor responses against your company’s legal playbook, highlights non-standard indemnification or liability clauses, flags risk levels to the legal team via workflow triggers, and updates CRM deal stages based on signature status.

Reads incoming contracts and flags anything unusual or risky for your legal team to look at, instead of someone reading every page of every contract by hand.

Syncs complex multi-year SaaS contracts, usage-based billing logs (Stripe/Metronome), and ERPs (Netsuite). It calculates ASC 606 revenue recognition schedules dynamically across distinct performance obligations, posts automated journal entries, and reconciles cash vs. deferred revenue daily.

Automatically works out how much revenue you're allowed to count each month from long contracts and subscriptions, and keeps your books accurate without manual spreadsheets.

Monitors real-time product telemetry (login drops, feature usage, API error rates, support ticket sentiment). When a churn risk threshold is breached, it auto-creates a high-priority CS ticket, generates an account-health summary via AI, pauses automated renewal emails, and triggers a retention playbook with personalized offer options for the account manager.

Spots customers who look like they're about to cancel — before they do — and automatically alerts your team with a plan to win them back.

Scans incoming PDF invoices via OCR, extracts line items, and cross-references them against Purchase Orders (POs) and goods received notes in the ERP. If figures match within a predefined tolerance, it schedules payment automatically; if mismatched, it routes the discrepancy directly to the issuing vendor and purchasing manager with highlighted line errors.

Checks incoming invoices against what you actually ordered and received, pays the ones that match automatically, and flags the ones that don't for a human to sort out.

Once an offer is signed in the ATS, the workflow provisions identity profiles in Okta/Azure AD, assigns role-based access control (RBAC) across 20+ SaaS apps, orders pre-configured hardware via vendor APIs, creates Jira onboarding tickets, schedules 30/60/90-day check-ins, and assigns mandatory compliance training modules.

The moment a new hire signs their offer, this sets up all their accounts and access, orders their laptop, and schedules their first few months of check-ins — automatically.

Connects web analytics, ad platform spend (Google, LinkedIn, Meta), product usage, and offline sales pipelines. It calculates multi-touch attribution (first-touch, last-touch, linear, W-shaped) on every closed deal, automatically reallocating ad budgets across campaigns based on actual ROI rather than vanity metrics.

Shows you which ads and campaigns actually led to real sales — not just clicks — and shifts your ad budget toward what's genuinely working.

Combines historical sales trends, promotional calendars, lead times, supplier capacity, and external weather/economic data. It forecasts demand, automatically drafts purchase orders when safety stock levels hit dynamic thresholds, sends POs to suppliers, and reserves warehouse space for incoming freight.

Predicts what stock you'll need and automatically orders it before you run out, instead of someone checking shelves and guessing.

Monitors SIEM/EDR logs for anomalous access or threat signatures. Upon detecting a high-severity event, it automatically isolates the affected endpoint from the network, revokes compromised user tokens in Identity Providers, captures system memory for forensics, and alerts the Security Operations Team on an emergency PagerDuty bridge.

If something suspicious happens on your network, it immediately locks down the affected device and alerts your security team — before a small problem becomes a big one.

Ingests incoming tickets, classifies intent/urgency using LLMs, fetches live context via APIs from product databases, executes backend database standard fixes (e.g., subscription resets, license key regenerations), writes a natural language resolution to the customer, and escalates to human agents only when confidence scores fall below threshold.

Reads incoming support tickets, solves the simple ones itself (like resetting an account), and only hands the tricky ones to a human.

Scans target company job boards, SEC filings, news releases, and tech stack detection tools. It passes these insights to AI prompts that craft unique, hyper-contextualized email messaging, verifies email deliverability, and drops the leads into tailored multi-channel outreach campaigns.

Researches potential customers and writes personalized outreach messages automatically, instead of your sales team spending hours researching each prospect by hand.

Parses incoming 100+ page Request for Proposal (RFP) documents, breaks them down into individual requirements, queries a centralized knowledge vector database for optimal answers, drafts response drafts, tags subject matter experts for unresolved sections, and compiles the final branded document.

Reads a huge proposal request, drafts answers to every question using your company's own knowledge, and only asks a human for help on the tricky parts.

Assesses return requests using machine learning risk models (address match, purchase history, return frequency). High-trust users receive instant auto-refunds and QR shipping codes, while high-risk requests are flagged for physical inspection before processing credit.

Instantly approves refunds for trustworthy customers, while flagging suspicious return requests for a human to check first.

Orchestrates code commits through automated unit testing, security vulnerability scans, build containerization, and canary deployment pipelines. If error rates increase during rollout, it automatically halts deployment, rolls back to the previous stable release, and assigns a high-priority incident ticket to the engineering team.

Tests and ships new software updates automatically, and if something breaks, it undoes the change by itself before customers are affected.

Upon receiving a Data Subject Access Request (DSAR) or deletion request, the workflow searches across production databases, analytics tools, CRMs, and cold storage, compiles or purges all personal identifiable information (PII), logs audit trails, and emails the user confirmation within legal time limits.

When someone asks "what data do you have on me" or "delete my data," this finds it everywhere it's stored and handles the request within the legal deadline — automatically.

Converts IoT sensor alerts or field inspection app data directly into work orders. It matches work requirements against contractor availability, skill requirements, and geo-location, dispatches the job automatically, tracks completion via mobile app updates, and handles subcontractor payment upon approval.

Turns a sensor alert or inspection report directly into a scheduled repair job, matched automatically to the right available contractor nearby.

Continuously monitors server loads, API latencies, and cloud spend. It automatically spins up or tears down computing instances, moves non-time-sensitive batch jobs to cheaper spot instances, and sends cost-optimization recommendations directly to DevOps channels.

Automatically adds computing power when you're busy and scales it back down when you're not, saving money without anyone having to watch a dashboard.

Pulls business credit bureau updates (Dun & Bradstreet) and internal invoice payment performance. If a client's risk score drops or payments delay, the system automatically adjusts net payment terms in the CRM/ERP, updates credit limits, and requires upfront payment on new orders.

Watches your customers' payment behavior and credit scores, and automatically tightens payment terms for anyone becoming a risk.

Monitors global cash balances, cross-border accounts receivables, and live FX market feeds. When currency exposures cross risk thresholds, it generates trading orders or triggers automated FX hedging transactions via banking APIs to lock in exchange rates.

Watches currency exchange rates and automatically protects your business from losses when you deal in multiple currencies.

Extracts data nightly across all core business tools (sales, marketing, product, support, finance) into a data warehouse (Snowflake/BigQuery). It runs statistical anomaly detection algorithms and generates an executive Slack/email summary explaining significant variances (e.g., "CAC rose 18% today due to a tracking bug in Campaign X").

Every night, it checks all your business numbers and sends you a plain-English summary of anything unusual — like "costs went up because of X" — before you even ask.