Input to outcome for every solution, with the components it really uses.
The model that reads, writes and answers. We choose it per solution and per customer.
A managed cloud AI service, or your own servers when data must stay in the building.
Storage, queues, databases and compute on AWS, Azure or Google Cloud, or on-premise.
Where a person reviews, approves or corrects. Shown in purple in every diagram.
Purchase orders in any format become checked, ERP-ready orders. A person approves each one.
Reads unstructured orders into structured lines; ranks customer and quote matches with reasons.
OCR for scanned and image-only PDFs, with confidence-based retry.
Runs the Parser, Matcher, Assembler and Validator agents and the eight-step workflow.
Decouples intake from processing; failed jobs are kept for replay, not lost.
Keeps source files and every step's state and decision.
Pricing, tax, surcharges, mandatory items and nine validation categories. Unit-tested.
Customer, quote and price lookup; order posting. The public demo uses a mock ERP.
Step-by-step review with Approve, Correct and Regenerate.
Every action is attributed to a user and logged.
An order cannot post twice; failures are visible and recoverable.
One assistant that answers product and service questions from every manual and file, with the source for each answer.
Answers come only from retrieved passages of the customer's own documents.
Reference implementation's model to be confirmed by the technical owner. Our Knowledge Base product uses large language models; a large language model on a managed cloud AI service is also supported.
Turns each passage into a vector so meaning-based search works.
Keeps passages, vectors and links back to the original page.
Improves retrieval and answers over time.
Documents stay in the agreed environment; hosting options include the customer's own cloud.
Typed, scanned and handwritten forms are read, every critical field is checked, and people only look at what needs them.
Reads every field and table on each rendered page, plus a tick-box ink check.
Second, independent reading of uncertain cells from the cropped image only. Can be switched off, leaving OCR plus rules.
IBAN checksum, BIC, German postcodes and dates, email. IBAN repair for common handwriting confusions (7 read as Z, 8 as S).
'Same as above' boxes, BIC agreement per bank, repeated names and towns must agree.
Upload, extraction, review state and export APIs.
Clickable field boxes on the page image, next-issue navigation, approve and export.
Each PDF goes to OCR once; repeat uploads cost nothing. No cloud object storage in the prototype.
Tracks the two errors a reviewer would never see: wrong values auto-accepted, and values shown empty.
An AI voice agent that answers calls, books appointments and captures leads around the clock, and hands complex calls to your team.
Natural, low-latency conversation.
Understands requests, chooses actions, writes summaries.
Speech recognition and voice output where used.
Connects real phone lines to the agent.
Business setup, conversation handling, tools.
Books into calendar or Outlook; leads to HubSpot, CRM or Zapier.
Each business's details and logs are kept separate.
Upload PDFs, contracts, policies and manuals. Anyone in the team asks in plain language and gets a precise answer with its source.
Writes answers from retrieved passages.
Meaning-based search across passages.
Available for customer deployments with cloud or residency requirements.
Upload, chat, citations.
Links every passage back to its document.
Chosen per customer.
AI agents write the high-level design (HLD), the low-level design (LLD) and the integration code, check each against your standards, and your experts approve every step.
Generation and validation. Azure cloud AI service is used where the customer requires it.
Multi-step generation, validation and repair loops.
Finds similar published reference designs to guide new ones.
One API for all agents, sessions and dashboards.
One page per agent, dashboards and reports.
Governance rules and standards checks, with reports.
Fetch requirements, publish designs.
Each role sees and approves its own step.
Scores generated documents against published reference documents.
The agent gathers everything behind a demand ticket (description, comments, attachments, linked items, estimates) and writes a structured requirements document that feeds straight into design.
Drafts requirement sections from ticket content.
Ticket, comments, attachments and linked items.
Contacts and IDs only from evidence; secrets redacted before any model call.
Shared sign-in, sessions and dashboards.
Writes the reviewed document to the team's space.
Talk to an expert 24/7. The first discovery call is free.