The intelligence infrastructure for domain-specific AI.
TRUSTED BY INNOVATIVE COMPANIES
AGENTS
AGENT
Call Sheet Agent
BUILD PROGRESS
Every day at 06:00
Scenes, cast, locations
Department dependencies and continuity rules resolved
34 recipients · awaiting sign-off
INCOMPLETE
Intelligence reaches the edge of what it understands and stops.
FORMED
Recapi discovers what is missing and develops it into structure.
COMPLETE
The whole system connects and can operate in the real world.
AI has intelligence.
The real world
requires understanding.
- AI can access information.
- It can remember what it learns.
- It can reason, generate and act.
But intelligence alone does not understand the environment where it operates. It does not automatically know what matters, what is missing, how information connects or what a specific real-world situation requires.
That missing layer is understanding.
SCRIPTS
412 pages
SCHEDULES
40 shoot days
CREW
118 people
FLOW STOPS
MEMORY
2 gaps open
RECAPI
Understanding
2 gaps closed · 6 layers live
DECISIONS
310 logged
DOCUMENTS
1,294 files
SYSTEMS
9 connected
PEOPLE
42 experts
WORKFLOWS
68 mapped
OPERATION
Call sheet
published · 34 sent
0 of 116 scenes shot · 116 still to go
No shoot day scheduled for today.
No shoot scheduled
There is no upcoming shoot
Intelligence alone stops short
It can read every source in the environment & still not know which of them matters to the outcome you asked for.
RISK LEVEL
1 Schedule · 1 Assets
116 scenes behind schedule
Scheduled on or before 3 Sept and still not marked shot.
Review schedule →
The gap is where work fails
What is missing rarely announces itself. It shows up as a decision no one can explain and a system no one trusts.
BY VALUE
₹8.4L · 100%
₹0
EXPOSURE AWAITING SIGN-OFF
₹8.4L
10 invoices held
PAID IN WINDOW
₹0
PAID TO DATE
₹7.5L
DAYS WITH PAYMENTS
0 of 30
AVERAGE PAYMENT DAY
₹0
Understanding closes it
Recapi develops the knowledge, context & relationships intelligence needs to operate meaningfully in the real world.
PRODUCT
Meet Recapi
From identifying what intelligence needs to know to building the context and workflows around it, Recapi brings the process into one connected environment.
Pre-Built Agents
Pick a ready-made agent to start from — it's added to your workspace as an editable draft you can customize.
Customer Support Agent
Technology
Answers common questions, troubleshoots issues, and escalates anything it cannot resolve to a human.
Sales Assistant
Retail
Qualifies inbound leads, answers product questions, and books demos with interested prospects.
Research Assistant
Education
Summarizes documents, answers questions from your knowledge base, and always cites its sources.
Start from a blank agent or a ready-made one. Either way it lands in your workspace as an editable draft, and the seven steps begin.
STEP 1 OF 7 · 5–10 MINUTES
Define What This Agent Should Achieve
Help us understand your agent's purpose. Be specific about what you want to automate.
Agent's Name
Agent's Goal
+ Add Another Goal
State the objective first
The build opens on intent, not on data. An assistant reads what you entered and names what is still too vague to build on.
Workflow Builder
Design how your AI agent processes and responds to interactions.
Components
Drag nodes from the sidebar to start building your workflow
Assemble the workflow
Triggers, actions, conditions and integrations on one canvas, so understanding becomes a procedure rather than a prompt.
STEP 7 OF 7 · FINAL REVIEW & DEPLOY
Audit & Deploy
Review your agent configuration and deploy it to your chosen environment.
Pre-Deployment Audit
Deployment Configuration
Prove it, then ship it
A pre-deployment audit runs every check before you release to staging, production or your own server.
STEP 01 · GOAL DEFINITION
Start with what the agent has to achieve
Every build begins with intent, not with whatever data happens to be available. You name the agent, state its goals and select the industry it will operate in. An assistant reads what you've entered and tells you what is still too vague to build on.
STEP 1 OF 7 · 5-10 MINUTES
Define What This Agent Should Achieve
Help us understand your agent's purpose. Be specific about what you want to automate and how success will be measured.
Agent's Name*
Agent's Goals* (1/10)
+ Add Another Goal
Industry*
STEPS 02–03 · TRAIN YOUR DATA & SIMULATION
Find the knowledge that isn't written down anywhere
This is where the missing layer gets built. Recapi runs a simulation against what you have uploaded, identifies the gaps that need clarification, and fills them through chat, documents or a video interview with the people who hold the knowledge. Nothing is trained until the gaps close.
Maximize Agent Accuracy
Start a simulation to discover missing data and complete your AI agent's training.
Start the interview to fill knowledge gaps. During the interview you can:
Chat — Have a conversation to provide missing information interactively.
Upload documents — Add files containing the required information.
Video interview — Join a video meeting to share detailed insights.
Share with Team
STEP 04 · MODEL TRAINING
Choose the model the task actually needs
GPT-4, a Recapi custom model that adapts to your business data, a lightweight model optimised for speed, or your own endpoint. Training model, accuracy focus, data weighting and temperature stay in your hands, with a live preview as you change them.
Model Training & Configuration
Configure and train your AI model with your business data
Choose Your Model
GPT - 4
RecommendedEnterprise-grade model with highest accuracy and reliability
Recapi custom
AdaptiveLearns and adapts specifically to your business data
Lightweight Model
FasterOptimized for speed with lower resource requirements
Bring Your Own
CustomConnect your own model via API endpoint
Training Configuration
Training Model
Accuracy Focus
Data Weighting
STEP 05 · WORKFLOW BUILDER
Turn understanding into a workflow that runs
Drag triggers, actions, conditions and integrations onto a canvas and configure each node. Understanding becomes an operating procedure the agent follows, rather than a prompt it has to interpret.
Workflow Builder
Design how your AI agent processes and responds to interactions
Components
Node Configuration
Click a node on the canvas to configure it
Drag nodes from the sidebar to start building your workflow
STEPS 06–07 · SECURITY CONFIG & AUDIT
Deploy on your terms, and prove it before you do
Authentication method, two-factor access, session timeouts, rate limiting, IP whitelisting and audit logging are all configured before launch. A pre-deployment audit runs against every check, and you ship to staging or production or to your own server, where your data never leaves your environment.
STEP 7 OF 7 · FINAL REVIEW & DEPLOY
Audit & Deploy
RefreshReview your agent configuration and deploy it to your chosen environment
Pre-Deployment Audit
No audit data yet. Click Refresh.
Deployment Configuration
Deployment Environment
Staging
Test environment for validation
ENTERPRISE
Deploy Recapi On Your Own Server
Your data stays on your infrastructure, never leaves your environment.
Deployment Guide
Pre-Deployment Checklist
All audit checks must pass before deploy. Review any warnings or errors.
Environment Selection
Start with staging to test your agent deploying to production.
Deployment Time
Deployment typically takes 2-5 minutes; a notification when complete.
Post-Deployment
Monitor your agent's performance on the dashboard after deployment.
See how Recapi can work for you
A short call with our team shows you how all of this looks inside your own environment.
Most AI starts with what it has. Recapi starts with what it needs to achieve.
The conventional approach begins with available data and asks what can we build with this? Recapi begins with the intended outcome and asks what does intelligence need to understand to achieve this?
Traditional AI
- Starts with available data
- Focuses on what AI can do
- Assume documents contain everything
- Require manual prompt tuning
- Focus on agent creation
- Limited workflow structure
- Usually tied to one model
- Often remain experimental
RECAPI AI
- Starts with the intended outcome
- Identifies what AI needs to understand
- Discover missing context through AI questions and guided calls
- Refine instructions through structured conversations
- Focus on agent reliability before deployment
- Design clear workflows with tasks and decisions
- Select models based on task requirements
- Forward Deployment into real environments
Building AI for the real world requires getting closer to it.
Recapi's Forward Deployment approach takes intelligence development beyond the screen & closer to the environments where it will actually operate. We work directly with organizations, teams and domain environments to understand the problem in context, before defining what intelligence should be built.
The objective is not to force a predefined AI solution into an industry. The objective is to understand the environment, identify the problem that matters and determine what AI needs to know to solve it.
We don't start with a predefined solution. We start by understanding what needs to be solved.
STATUS
TYPE
CATEGORIES
Log into LinkedIn
Access your LinkedIn account using your credentials.
Review the Trending Post
Click on the trending post to read and understand th…
+ Create
Identify Trending Posts
Look for the section that highlights trending posts or…
+ Create
Crawl Latest Invoice
Retrieve the most recent invoice from the system.
+ Create
Understand the environment
Study the systems, workflows, people & conditions surrounding the problem.
Work with domain experts
Learn from the people and expertise that define how the environment operates.
Identify the intelligence gap
Determine the difference between what the outcome requires and what AI currently understands. This is the gap everything else is built to close, found before a line of the solution exists, not after it ships.
Develop the right understanding
Build intelligence around the knowledge & context that environment requires.
Evolve with reality
Continue developing understanding as the environment and requirements change.
See what
Recapi built
Three environments, three products, one infrastructure underneath. What changed each time was not the need for understanding, it was what needed to be understood.
Film & production
Scripts, schedules, cast, locations & budgets read as one dependent system, so a missing shot is a gap in the plan.
Workforce & scheduling
Demand read weeks ahead & held against the roster that exists. Sick calls re-solve in seconds.
Organizational operations
Approvals & workflows running on a shared understanding, every external action pausing for sign-off.
One infrastructure. Different forms of intelligence.
The same underlying infrastructure takes different forms depending on the environment it enters. What changes is not the need for understanding. What changes is what needs to be understood. Everything below is running in production.
Build the production that holds together
Film production involves creative decisions, scripts, schedules, cast, locations, departments, budgets & constantly changing dependencies. Recapi builds intelligence infrastructure around that complexity, systems that understand how the parts of a production connect, so a missing shot reads as a gap in the plan rather than a blank row in a spreadsheet.
0 of 116 scenes shot · 116 still to go
No shoot day scheduled for today.
116 scenes behind schedule
Day 41 of 40 · 100% of the shoot behind us
No shoot scheduled for today
There is no upcoming shoot day on the schedule.
View full scheduleRISK LEVEL
1 Schedule · 1 Assets
Scheduled on or before 3 Sept and still not marked shot.
Review schedule →
Oldest is props: TV.
Review assets →
ELS · crane · High Angle
Establishes the overall setting and mood
of the farmhouse at night. - A wide shot of…
Break a scene into shots
The system already understands lighting setup, camera framing and continuity references, and flags which shots remain unresolved.
CREW CALL
18:00
DATE
Wednes… 2026
TOTAL PA…
1.25
BASE LOCATION
DELHI FARMHOUSE
PRODUCTION NOTES
Resolve the day
Crew call, locations, shift windows and wrap time settle into one plan because the system knows what each depends on.
SCRIPT PROGRESS
0%↘ -100% vs plan
0 of 116 scenes shot · 116 still to go
TODAY'S SHEET
0
No shoot day scheduled for today.
No shoot scheduled
There is no upcoming shoot
Read the whole production
Progress, spend and exposure roll up continuously, so the state of the production is never assembled by hand.
What Recapi built for workforce operations.
Recapi's understanding infrastructure was applied to workforce operations to connect people, demand and operational requirements in one intelligent system. The result brings workforce deployment, forecasting and decision-making into one connected environment.
Forecast Workforce Demand
Anticipate workforce needs by comparing projected demand with scheduled capacity to identify staffing gaps.
Welcome back, Dr.2 👋
Tuesday, August 19th 2025 · 8:37 PM
📊 Review Analytics
Comprehensive insights and performance metrics.
View Analytics
✦ AI Forecast
Predictive analysis and smart forecasting.
View Forecast
🗓 Open Shifts
See Workforce Operations in One Place
Bring workforce activity, shifts & insights into one view, so teams see what needs attention.
AI Schedule Review
Review the AI-generated schedule before applying it to your calendar
Conflict Detection & Resolution
⟳ Re-checkFilter Conflicts By Shift Type
No conflicts detected with all shifts
Change the filter above to check for conflicts.
Review & Apply AI-Generated Schedules
Generate schedules with AI, review conflicts and recommendations, & apply changes with confidence.
Which capability would you like to see?
Find New Customers. Send Emails. Book More Meetings.
Stop spending hours looking for potential customers. Orion finds businesses that match your ideal customer, writes personalized emails, follows up automatically, and books meetings when someone is interested.
How It Works
- 1Tell Orion who you want to sell to.
- 2It finds businesses that match your criteria.
- 3It writes and sends personalized emails.
- 4It follows up automatically.
- 5Interested prospects book a meeting on your calendar.
Find New Customers. Send Emails. Book More Meetings.
Stop spending hours looking for potential customers. Orion finds businesses that match your ideal customer, writes personalized emails, follows up automatically, and books meetings when someone is interested.
How It Works
- 1Tell Orion who you want to sell to.
- 2It finds businesses that match your criteria.
- 3It writes and sends personalized emails.
- 4It follows up automatically.
- 5Interested prospects book a meeting on your calendar.
The knowledge AI needs is rarely in one place.
It already exists across organizations and environments. In documents. Inside software systems. With domain experts. Across conversations. Within workflows. And in the decisions people make every day.
Recapi brings these sources into the process of developing understanding, connecting what is relevant and identifying what is still missing.
Start with what exists. Discover what is missing.
Interview the people who know
Gaps close through chat, documents or a recorded session with the person who holds the knowledge nobody wrote down.
CREW CALL
18:00
DATE
Wednesday, M…
2026
TOTAL PAGES
1.25
BASE LOCATION
DELHI FARMHOUSE
PRODUCTION NOTES
Read the systems already running
Operational data keeps its meaning instead of arriving as rows that need re-explaining.
Model Training & Configuration
Configure and train your AI model with your business data
Choose Your Model
GPT - 4
RecommendedModel option for your data
Recapi custom
AdaptiveModel option for your data
Lightweight Model
FasterModel option for your data
Bring Your Own
CustomModel option for your data
Training Configuration
Training Model
Accuracy Focus
Eval Weighting
Temperature
ENTERPRISE
Deploy Recapi On Your Own Server
AI Suggestions
Config recommendation based on your data profile.
Live training preview updates as you change settings.
Weigh what matters most
Accuracy focus, data weighting and model choice stay in your hands, with a live preview as you change them.
AI is moving closer to the real world.
The first generation of AI answered questions. The next generation is entering workflows, organizations and operational environments. The generation after that will move even further. Into machines. Autonomous systems. Industrial environments. And eventually, the physical world.
As AI moves closer to reality, intelligence alone will not be enough. It will need to understand the environment around it.
TODAY
Digital Intelligence
AI operates through software & information.
NOW
Organizational Intelligence
AI understands people, knowledge, workflows and operations.
NEXT
Operational Intelligence
AI operates within increasingly complex real-world environments.
FUTURE
Physical Intelligence
AI develops the understanding required to interact with physical systems and environments.
Recapi is building toward the infrastructure that makes this possible.
Works With Your Existing Tech Stack
Trusted by Builders and Innovators
Mohamed A. Yousuf
Founder, Smartworkforce AI
Recapi.ai stands out in how it approaches AI systems. Instead of just generating agents, it focuses on understanding the workflows and knowledge behind them. That difference makes the agents far more reliable and useful.
Eleazar Lua
Founder, Vacanzastays
Recapi.ai stands out in how it approaches AI systems. Instead of just generating agents, it focuses on understanding the workflows and knowledge behind them. That difference makes the agents far more reliable and useful.
Frequently Asked Questions
Everything you need to know about building understanding infrastructure.
Recapi Is AI Understanding Infrastructure For The Real World. It Develops The Knowledge, Context And Domain Understanding AI Needs To Operate Meaningfully Within Specific Environments.
Don't Miss the Next Insight
Explore how modern AI systems are built, through deep dives, case studies, and practical insights from real-world implementations.
Weekly newsletter only. No spam, unsubscribe at any time.