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ForwardMax
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FMAI engineering & consulting

We design AI systemsthat elevate how yourbusiness operates.

ForwardMax designs, builds and deploys custom AI — agents, document workflows and knowledge systems — for established businesses. Built on your data, integrated with your systems, measured against your numbers.

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30 minutes with an engineer. No slide deck.

How we work with clients

  • 01

    Production, not prototypes

    We engineer systems your team relies on daily — monitored, tested, maintained.

  • 02

    Built around your domain

    Your workflows, data and constraints shape the design. No templates.

  • 03

    Confidential by default

    Your data and strategy stay yours. Access is scoped to what the work needs.

  • 04

    Partnership after launch

    AI systems improve with use. We stay to refine, extend and adapt them.

01The problem

Most AI work stalls between the demo and the day-to-day.

A promising pilot is easy. A system that holds up against messy data, real users and existing software is engineering work — and that is where most initiatives quietly stop.

  1. 01

    The pilot never ships

    Proofs of concept impress in a meeting, then hit security review, edge cases and integration work nobody planned for.

  2. 02

    Knowledge is scattered

    The answers live in inboxes, PDFs, spreadsheets and people's heads — not in a form a model can use reliably.

  3. 03

    Workflows are still manual

    Teams re-key data between systems and chase approvals by email, so AI ends up as one more tab instead of part of the process.

  4. 04

    Nobody owns it after launch

    Models drift, prompts break and costs creep. Without evaluation and monitoring, trust erodes and usage falls away.

02Services

From the first workflow to a system your team relies on.

Four ways we engage. Most clients start with one high-value workflow and expand from there.

  1. 01

    AI strategy & roadmap

    Know which work is worth automating — and what it will take.

    We map your workflows, data and systems, size the opportunities and turn them into a sequenced plan with clear success measures.

    Discuss this: AI strategy & roadmap(opens in a new tab)
    • Opportunity assessment
    • Architecture & build-vs-buy
    • Value and risk sizing
    • Phased roadmap
  2. 02

    Agents & workflow automation

    Hand repetitive, rules-heavy work to systems that act — with people in control.

    Agents that read, decide and act across your tools: triaging requests, processing documents, updating records, escalating exceptions for review.

    Discuss this: Agents & workflow automation(opens in a new tab)
    • Tool-using agents
    • Document processing
    • Back-office automation
    • Human-in-the-loop review
  3. 03

    Knowledge & decision systems

    Put institutional knowledge and data in front of the people who need it.

    Assistants and search grounded in your documents and data, with permissions respected and sources cited — so answers can be checked.

    Discuss this: Knowledge & decision systems(opens in a new tab)
    • Retrieval (RAG) & AI search
    • Internal copilots
    • Decision support & reporting
    • Permission-aware access
  4. 04

    AI engineering & operations

    Keep AI systems accurate, observable and affordable in production.

    The engineering that makes AI dependable: evaluation suites, model integration, monitoring, cost control and deployment inside your environment.

    Discuss this: AI engineering & operations(opens in a new tab)
    • Evaluation & testing
    • Model integration
    • Observability & cost control
    • Production deployment

Not sure where to start? That's what the first call is for.

Book a discovery call(opens in a new tab)

03What changes

Same request. Different operating model.

One customer request, followed through five stages — as it is often handled today, and as it runs once an AI system is part of the workflow.

  1. 01 Intake

    TodayRequests land in a shared inbox and wait for someone to triage them.

    With AIEach request is read, classified and routed the moment it arrives.

  2. 02 Research

    TodayStaff search drives, old emails and three systems for context.

    With AIRelevant history, documents and account data are assembled with sources.

  3. 03 Draft

    TodayA response is written from scratch, quality depending on who picks it up.

    With AIA draft is prepared to your standards, ready for review.

  4. 04 Decide

    TodayApprovals are chased by email; exceptions get missed.

    With AIRoutine cases flow through; exceptions are flagged to the right person.

  5. 05 Record

    TodayOutcomes are re-keyed into the CRM — if someone remembers.

    With AISystems of record update automatically, with a full audit trail.

04Work

The kind of systems we ship.

Representative engagements, described the way we scope real ones: the problem, what we changed, what we built and how success is measured.

Illustrative engagements. Client case studies are published only with permission — we're happy to walk through relevant work on a call.

Operations · Finance

Invoice and document intake that clears itself

Problem

Accounts payable re-keys supplier invoices from PDFs and email into the ERP, matching each one to a purchase order by hand.

Intervention

Automate extraction and matching for routine invoices; route only variances and new suppliers to a person.

System

  • Document extraction
  • PO matching rules
  • Review queue
  • ERP integration

Outcome

The team reviews exceptions instead of typing, and every posting carries an audit trail.

Measured by: Straight-through rate · Cycle time · Error rate

Professional services

A knowledge assistant grounded in fifteen years of work

Problem

Proposals and client answers depend on a few senior people who remember where past work lives.

Intervention

Index past proposals, reports and policies with permissions intact; answer questions with cited sources.

System

  • Permission-aware retrieval
  • Cited answers
  • Proposal drafting
  • Usage analytics

Outcome

Anyone on the team can find precedent and draft from it, with sources they can verify.

Measured by: Time to first draft · Answer accuracy · Weekly active users

Customer operations

Support triage that routes, drafts and escalates

Problem

A growing request queue is triaged manually; urgent issues wait behind routine ones.

Intervention

Classify and prioritise every request, draft replies for common cases and escalate risk early.

System

  • Classification agent
  • Reply drafting
  • Escalation rules
  • Helpdesk integration

Outcome

Urgent requests reach the right person first; routine replies are reviewed, not written.

Measured by: First-response time · Routing accuracy · Resolution rate

05Use cases

Where AI pays off first.

The best starting points are frequent, rules-heavy and data-rich — work your team already knows well enough to describe.

  • Documents

    Intelligent document processing

    Contracts, invoices, forms and reports turned into structured, validated data.

  • Knowledge

    Enterprise knowledge assistants

    Answers from your policies, past work and records — with sources cited.

  • Operations

    Workflow agents

    Multi-step processes that read, decide and update systems, escalating exceptions.

  • Customers

    Support triage & drafting

    Requests classified, prioritised and drafted for review in your helpdesk.

  • Teams

    Operational copilots

    Assistants inside the tools people already use, aware of their context.

  • Search

    AI search across systems

    One place to find what lives in drives, wikis, tickets and databases.

  • Revenue

    Sales & proposal automation

    Research, qualification and first drafts prepared before the meeting.

  • Decisions

    Decision support & reporting

    Patterns and narrative summaries surfaced from the data you already collect.

06Agents

Agents, deployed where the work is.

Each agent has a job, a set of tools, a boundary on what it may do alone, and a person who owns the exceptions. Here is how that looks across functions and industries.

Illustrative deployments. Systems, thresholds and timings are set during discovery, against your data and your policies.

01 / 13

  • Fig. 01.01Autonomy: Acts with approval

    Finance · Accounting

    Month-end close agent

    Reconciles ledgers against bank and subledger data, chases missing support and drafts the adjusting entries.

    1. Pull balances
    2. Reconcile
    3. Investigate gaps
    4. Controller reviewPerson
    5. Post entries

    Activity

    1. 06:02Reconciled 412 of 431 bank lines
    2. 06:0419 open items · 3 need support
    3. 06:09Drafted 6 accruals for review
    Connects to
    • ERP
    • Bank feeds
    • Shared drive
    Hands to a person when

    An entry changes a balance, or an item has no supporting document.

    Measured by

    Days to close · Unreconciled items · Manual entries

  • Fig. 01.02Autonomy: Acts within limits

    Procurement · Manufacturing

    Supplier follow-up agent

    Watches open purchase orders, chases late confirmations and reads replies to update delivery dates.

    1. Scan open POs
    2. Contact supplier
    3. Read reply
    4. Buyer decisionPerson
    5. Update ERP

    Activity

    1. 08:1511 POs past confirmation date
    2. 08:16Sent 11 follow-ups in supplier language
    3. 11:40PO-22941 slips 9 days → buyer alerted
    Connects to
    • ERP
    • Shared inbox
    • Supplier portal
    Hands to a person when

    A delay threatens a production date or a supplier stops replying.

    Measured by

    Confirmed-on-time rate · Buyer hours spent chasing · Late-line visibility

  • Fig. 01.03Autonomy: Acts within limits

    People · HR operations

    HR service agent

    Answers policy questions with sources, completes routine requests and keeps sensitive cases with HR.

    1. Understand request
    2. Check policy
    3. Sensitive?
    4. HR partnerPerson
    5. Complete request

    Activity

    1. 10:12Leave balance request → answered from HRIS
    2. 10:14Employment letter issued · template v4
    3. 10:21Grievance detected → routed to HR partner
    Connects to
    • HRIS
    • Policy library
    • Chat and email
    Hands to a person when

    The topic is a grievance, health, pay dispute or anything the policy does not cover.

    Measured by

    Self-service rate · Time to resolution · Escalation accuracy

  • Fig. 01.04Autonomy: Drafts for review

    Legal · Commercial contracts

    Contract review agent

    Compares incoming contracts to your playbook, marks deviations and proposes the fallback clause.

    1. Read contract
    2. Map clauses
    3. Compare to playbook
    4. Counsel reviewPerson
    5. Send redline

    Activity

    1. 14:20Parsed 38 pages · 41 clauses mapped
    2. 14:216 deviations · 2 outside fallback range
    3. 14:22Redline drafted with playbook references
    Connects to
    • Contract repository
    • Playbook
    • Email
    Hands to a person when

    Every redline. The agent prepares it; counsel decides what goes out.

    Measured by

    Review turnaround · Playbook coverage · Counsel edit rate

  • Fig. 01.05Autonomy: Acts with approval

    IT · Service desk

    Access and onboarding agent

    Turns a new-starter or access request into the right accounts and permissions, with every grant on record.

    1. Read request
    2. Map role to access
    3. Manager approvalPerson
    4. Provision
    5. Confirm and log

    Activity

    1. 09:01Starter: Analyst, Treasury · role template found
    2. 09:029 systems mapped · 2 need manager approval
    3. 09:37Approved · 9 accounts provisioned
    Connects to
    • Identity provider
    • ITSM
    • HRIS
    Hands to a person when

    The access is privileged, outside the role template, or the requester is unverified.

    Measured by

    Time to first-day ready · Access exceptions · Tickets avoided

  • Fig. 01.06Autonomy: Drafts for review

    Sales · B2B services

    Account research agent

    Builds a pre-meeting brief from CRM history, filings and news, then drafts the follow-up and updates the record.

    1. Gather sources
    2. Summarise account
    3. Draft brief
    4. Rep reviewPerson
    5. Update CRM

    Activity

    1. 07:30Meeting 10:00 · Halden Freight · 7 sources
    2. 07:31Brief ready · 2 open threads flagged
    3. 11:05Follow-up drafted from call notes
    Connects to
    • CRM
    • Calendar
    • Public filings
    Hands to a person when

    Always. The rep owns the relationship and approves what is sent.

    Measured by

    Prep time per meeting · CRM completeness · Follow-up speed

  • Fig. 01.07Autonomy: Acts within limits

    Customer operations · Retail and e-commerce

    Returns and refunds agent

    Resolves return requests against policy, issues refunds inside set limits and spots abuse patterns.

    1. Read request
    2. Check order and policy
    3. Within limit?
    4. Agent reviewPerson
    5. Refund or reply

    Activity

    1. 13:44Order 88213 · delivered 6 days ago · eligible
    2. 13:44Refund $42.00 · within auto-approve limit
    3. 13:514th claim this month → held for review
    Connects to
    • Order system
    • Payments
    • Helpdesk
    Hands to a person when

    The amount is over the limit, the pattern looks unusual or the customer is upset.

    Measured by

    First-contact resolution · Refund leakage · Handle time

  • Fig. 01.08Autonomy: Acts with approval

    Claims · Insurance

    First-notice-of-loss agent

    Captures the claim, checks coverage, requests what is missing and routes it with a clean file.

    1. Capture claim
    2. Check coverage
    3. Request documents
    4. Adjuster reviewPerson
    5. Open claim file

    Activity

    1. 16:08Claim received by chat · water damage
    2. 16:09Policy active · peril covered · $1,000 deductible
    3. 16:12Photos and invoice requested from claimant
    Connects to
    • Policy admin
    • Claims system
    • Customer chat
    Hands to a person when

    Coverage is unclear, the claim is large, or fraud indicators appear.

    Measured by

    Time to first contact · File completeness · Adjuster touch time

  • Fig. 01.09Autonomy: Drafts for review

    Revenue cycle · Healthcare

    Prior authorisation agent

    Assembles clinical evidence for each payer's rules, submits requests and tracks them to a decision.

    1. Read order
    2. Gather evidence
    3. Match payer rules
    4. Staff reviewPerson
    5. Submit and track

    Activity

    1. 08:50Order: MRI knee · payer rules v2026.3
    2. 08:51Evidence found in 2 of 3 required notes
    3. 08:52Gap flagged · staff asked for therapy record
    Connects to
    • EHR
    • Payer portals
    • Document store
    Hands to a person when

    Every submission and every denial. Clinical judgement stays with clinicians.

    Measured by

    Submission turnaround · First-pass approval rate · Staff hours per case

  • Fig. 01.10Autonomy: Drafts for review

    Compliance · Banking and fintech

    KYC onboarding agent

    Collects documents, screens against watchlists and registries, and assembles the risk file for the analyst.

    1. Collect documents
    2. Verify identity
    3. Screen and research
    4. Analyst decisionPerson
    5. Open account

    Activity

    1. 11:18Registry match · 2 directors identified
    2. 11:19Screening: 1 possible name match
    3. 11:21Risk file assembled · sources attached
    Connects to
    • Core banking
    • Screening provider
    • Company registries
    Hands to a person when

    Every decision. The agent prepares the file; an analyst approves or declines.

    Measured by

    Onboarding time · Analyst hours per file · Rework rate

  • Fig. 01.11Autonomy: Acts within limits

    Operations · Logistics

    Shipment exception agent

    Detects delays across carriers, rebooks within rules and tells the customer before they ask.

    1. Watch tracking
    2. Detect delay
    3. Rebook in rules
    4. Planner reviewPerson
    5. Notify customer

    Activity

    1. 05:22Port congestion · 14 containers at risk
    2. 05:249 rebooked within cost limit
    3. 05:255 need premium freight → planner
    Connects to
    • TMS
    • Carrier APIs
    • Customer email
    Hands to a person when

    The fix costs more than the limit or misses a contracted delivery window.

    Measured by

    On-time delivery · Exception handling time · Proactive notification rate

  • Fig. 01.12Autonomy: Acts with approval

    Maintenance · Manufacturing

    Maintenance planning agent

    Reads equipment alerts and work-order history, drafts the job and slots it into planned downtime.

    1. Read alerts
    2. Diagnose from history
    3. Draft work order
    4. Planner approvalPerson
    5. Schedule

    Activity

    1. 02:10Press 4 · vibration trend above baseline
    2. 02:113 similar cases → bearing replacement
    3. 02:12Work order drafted · fits Sunday window
    Connects to
    • CMMS
    • Sensor data
    • Spares inventory
    Hands to a person when

    The line must stop, safety is involved or parts are not in stock.

    Measured by

    Unplanned downtime · Planned vs reactive work · Emergency repair cost

  • Fig. 01.13Autonomy: Drafts for review

    Leadership · Analytics and reporting

    Weekly reporting agent

    Refreshes the numbers, investigates what moved and writes the commentary leaders read on Monday.

    1. Refresh data
    2. Detect movement
    3. Trace the cause
    4. Analyst reviewPerson
    5. Publish

    Activity

    1. 05:0014 sources refreshed · 2 stale
    2. 05:03Margin down 1.8 pts · traced to 2 accounts
    3. 05:05Commentary drafted with queries attached
    Connects to
    • Warehouse
    • BI tool
    • Email
    Hands to a person when

    A figure fails a data check or the explanation is uncertain.

    Measured by

    Hours to produce · Question-to-answer time · Issues caught before publishing

07Approach

Small steps, real systems, clear decisions.

Each phase ends with something you can evaluate and a decision on whether to continue. No long contracts before value is proven.

Start with a discovery call(opens in a new tab)

  1. Step 01

    Discover

    We learn the workflow, the data and the systems around it, and agree on which opportunity is worth pursuing first.

    Output Prioritised opportunity and success measures

  2. Step 02

    Design

    We define the experience, architecture, guardrails and how quality will be evaluated — before building at scale.

    Output Architecture, evaluation plan and scope

  3. Step 03

    Prototype

    We build a working version against your real data, test it with the people who will use it and measure it honestly.

    Output Working prototype with measured results

  4. Step 04

    Deploy

    We harden it for production: integrations, permissions, monitoring, fallbacks and the training your team needs.

    Output Production system in your workflow

  5. Step 05

    Scale

    We improve accuracy and reliability with real usage, extend to adjacent workflows and support your team's ownership.

    Output Ongoing improvement and expansion

08Technology & trust

Model-agnostic engineering. Enterprise discipline.

We choose models and infrastructure for the job, not for a partnership. And we treat security and oversight as part of the design, not a review at the end.

Stack we work across

Models
OpenAI
Anthropic
Google Gemini
Open-weight models
Cloud
AWS
Microsoft Azure
Google Cloud
Orchestration
LangGraph
LangChain
Custom agent runtimes
Data & retrieval
Postgres + pgvector
Vector databases
Knowledge graphs

Security & responsible AI

  • Your data stays scoped

    Access limited to what the system needs; no use of your data to train shared models.

  • Deployable in your environment

    Systems can run in your own cloud account when your policies require it.

  • People stay in control

    Approval steps for consequential actions, with clear escalation paths.

  • Measured, not assumed

    Evaluation suites track accuracy before and after every change.

  • Observable in production

    Logging, tracing and cost monitoring so behaviour can be audited.

  • Permission-aware

    Answers respect the access rights your systems already enforce.

09FAQ

Questions we hear before every project.

Something else? hello@forwardmax.ai

  • It depends on scope, but we work in short phases. Discovery and design typically take weeks, not months, and a working prototype on your real data follows soon after. You see results before committing to a full build.

  • Every engagement is scoped to the work. After the discovery call we propose a defined first phase with a clear price and deliverables, so you can evaluate value before investing further.

  • Yes — that is most of the work. We connect to the ERPs, CRMs, helpdesks, document stores and databases you already run, through their APIs or established integration patterns.

  • Yes. We can lead delivery, work alongside your engineers, or build the first system and hand over ownership with documentation and training.

  • Access is scoped to what the work requires, data is never used to train shared models, and we follow your security policies. Our privacy practices are set out in our privacy policy.

  • Yes. Where your requirements call for it, we design systems to run inside your own AWS, Azure or Google Cloud account.

  • Both, in that order. Prototypes exist to prove value quickly; the goal is always a production system your team relies on, with monitoring and evaluation in place.

  • We are model-agnostic: OpenAI, Anthropic, Google and open-weight models, chosen per task for quality, cost, latency and data requirements — and designed so models can be swapped as they improve.

10Start a conversation

Have a workflow worth automating?

Tell us about the work. In 30 minutes you'll get an engineer's honest read on what's feasible, what it would take and where to start.

Book a discovery call(opens in a new tab)hello@forwardmax.ai

What happens on the call

  1. 01A 30-minute call with an engineer, not a sales pitch
  2. 02An honest view on feasibility, risk and value
  3. 03A suggested first phase — if there's a fit